Sustainability Practices In The Turkish Construction Sector Environmental Sciences Essay

Abstract. The Turkish building services bunch is the thirteenth largest in the universe in footings of exports and has demonstrated really high growing of 63 % in international projects. Katsarakis et Al ( 2007 ) split this bunch into two parts and call them as the lower-quality domestic-only set of houses and the higher choice international houses. On the domestic side, there are more than 30,000 active local houses ( TCA, 2009 ) . On the international houses ‘ side, there are over 140 houses, 23 of which are among the 225 largest building companies worldwide in footings of abroad activities per ENR 2008 listing. This degree of activity, peculiarly the international activity, places upon the Turkish building bunch a duty to guarantee good working conditions for all its employees and to play a polar function in continuing the environment, extenuating bing polluted countries, salvaging natural resources such as H2O, energy and natural stuffs. This paper examines, through a liter ature survey, the current degree of sustainability apprehension in the Turkish building sector. The survey concludes that the degree of sustainability apprehension and hence its execution is unstructured, bit-by-bit, and inappropriate for the prima regional function that the Turkish building bunch will play. The paper concludes that a more holistic attack is required, which will necessitate political policy and larning from best pattern from other states and immensely increased instruction and preparation in the constructs of sustainability. Keywords: Construction bunch, policy, scheme, Sustainability, Turkey 1. Introduction Sustainability is more and more going a cardinal concern of every person. It is a concern that has grown out of a wider acknowledgment that lifting populations and economic development are endangering a progressive debasement of the Earth ‘s resources per CIOB ( 2009 ) . The building, care and usage of edifices have significant impact on our environment and are presently lending significantly to irreversible alterations in the universe ‘s clime, atmosphere and ecosystem. Endeavoring for sustainability is a uninterrupted procedure of alteration. The building industry is confronting ever-increasing demands to better its sustainability public presentation. Sustainable development applies at the political and macro economic degree to communities. The clients and stakeholders of the building industry demand betterments of its patterns and its public image. Karacay ( 2003 ) stated that the epoch of â€Å" more production-more ingestion † is over and a great trade of accent should be to sustainability for uninterrupted sustainable economical growing and development. Sustainable building is a manner for the building industry to travel towards accomplishing sustainable development, taking into history environmental, socio-economic and cultural issues. Specifically, it involves issues such as design and direction of edifices, stuffs and edifice public presentation, energy and resource ingestion – within the larger orbit of urban development and direction. In this paper, sustainability of the substructure undertakings will be concentrated on. Recent publications related to sustainable building in the context of Private Finance Initiative ( PFI ) route undertakings ( AkbA ±yA ±klA ± & A ; Eaton, ( 2009a and B ) ) and sustainable substructure developments in the instance of Public-Private Partnership ( PPP ) ( Eaton & A ; AkbA ±yA ±klA ± , ( 2008 ) ) are available. 2. Sustainability Sustainability, as stated by Werbach ( 2009 ) , is more than â€Å" green † ; it is concern agencies, above all, guaranting that the concern thrives in the long term and takes into history every dimension of the concern environment. Sustainability is the concern with long-run profitableness. Sustainability needs a scheme behind that includes all the supply concatenation, top direction engagement and support ; and it relates all the concern organisation. We are in an epoch that the Nature and the equilibrium in the Nature that will govern and regulate the developments in our industry. We will be concerned more than of all time in the value adding in the building concern that will be a combination between sustainability ( societal, economic, environmental and cultural ) , efficiency and effectivity. In Werbach ‘s ( 2009 ) words, â€Å" Until the 1980 ‘s concern leaders used the word sustainability to intend a company ‘s ability to increase its net incomes stea dily ( Werbach, 2009 ) . Sustainability represents the best technology attack of all – the acknowledgment that no undertaking exists in a vacuity, but in a societal and natural context that affects the undertaking and is affected by it in bend. If we take this holistic position of technology, which involves esteeming the natural and human environment in the design, building and operation of our undertakings, we find distinguishable benefits in footings of quality, proficient inventions, and long-run societal, economic and environmental returns ( Tanal ( 2004 ) ) . Harmonizing to Werbach ( 2009 ) , a sustainable concern means a concern that can boom in the long term. Brundtland Report ( 1987 ) , besides known as Our Common Future, alerted the universe to the urgency of doing advancement toward economic development that could be sustained without consuming natural resources or harming the environment. The study was published by an international group of politicians, civil retainers and experts on the environment and development, and provided a cardinal statement on sustainable development specifying it as â€Å" development that meets the demands of the present without compromising the ability of future coevalss to run into their ain demands † . The study besides suggested that equity, growing and environmental care are at the same time possible and that each state is capable of accomplishing its full economic potency whilst at the same clip heightening its resource base. Furthermore, in the same survey it is reported that accomplishing the equity and sustainable growing would necessitate technological and societal alteration. In stead to this fact, Sage ( 1998 ) stated that sustainability necessitates the development of enlightened establishments and substructure and appropriate direction of hazards, uncertainnesss, and knowledge imperfectnesss to guarantee intergenerational equity, intergenerational equity, and preservation of the ability of Earth ‘s natural systems to function world. As defined by Chaharbaghi & A ; Willis ( 1999 ) and presented in a study on sustainability by FIEC ( 2005 ) , sustainable development is a construct based on a construction which stands on 3 pillars, viz. economic, societal and environmental. This inter-related model is shown in Figure 1. Fig. 1. Three pillars of sustainability ( Chaharbaghi & A ; Willis ( 1999 ) in â€Å" Managing Knowledge in the Context of Sustainable Construction † ITcon Vol. 11 ( 2006 ) ) 3. The building industry and sustainability Sustainable building can be defined as a building procedure which incorporates the basic subjects of sustainable development ( Parkin ( 2000 ) , Chaharbaghi & A ; Willis ( 1999 ) , Sage ( 1998 ) ) . Such building procedures would therefore convey environmental duty, societal consciousness, and economic profitableness aims to the bow in the reinforced environment and installations for the wider community ( Langston & A ; Ding ( 2001 ) , Miyatake ( 1996 ) , Raynsford ( 2000 ) ) . Companies are the cardinal elements of modern economic life and they have an of import function in conveying about the alterations needed for sustainable development. Harmonizing to Wilson ( 2003 ) â€Å" corporate sustainability is a concern attack that creates long term stockholder value by encompassing chances and pull offing hazards deducing from economic, environmental and societal developments. While corporate sustainability recognizes that corporate growing and profitableness are of import ; it besides requires the corporation to prosecute social ends, specifically those associating to sustainable development such as environmental protection, societal justness and equity and economic development † . Werbach ( 2009 ) argues that, if imagined and implemented to the full, sustainability drives a bottom-line scheme to salvage costs, a top-line scheme to make a new consumer base, and a endowment scheme to acquire, maintain, and develop originative employees. The three pillars or as named by Fiksel ( 2001 ) , the â€Å" ternary underside line † , economic prosperity and chance societal equity and quality of life and ecological resource saving represents sustainability as an organisational committedness to accomplishing competitory advantage through the strategic acceptance and development of ecologically and socially supportive production procedures, merchandises and services and advanced human resource direction patterns. ( Dunphy et al ( 2003 ) ) . For those organisations prosecuting sustainability, it is cardinal to their corporate schemes and a critical ingredient in how they assess their effectivity. A survey by Dunphy ( 2004 ) states that â€Å" sustainability consequences from activities which extend the socially utile life of organisations, heighten the planet ‘s ability to keep and regenerate the viability of the biosphere and protect all life species, enhance society ‘s ability to keep itself and to work out its major jobs, keep a nice degree of public assistance for present and future coevalss of humanity † The building industry and the reinforced environment must be counted as two of the cardinal countries required to achieve a sustainable development in societies. It is a widely known fact that, the edifices are responsible for over 40 % of all the waste produced in the European Union. In developing and passage economic systems, building has a immense part to the Gross National Product ( GDP ) ; but this has to be done in a more sustainable mode while bettering the quality of life and making wealth. However, sustainable building adopts different precedences in different states. There are widely different positions and readings between developed and passage and developing states. The developed economic systems are in a place to give more attending to making a more sustainable constructing stock by upgrading, by new developments or the usage of new advanced engineerings. All public procurance should be made consistent with authorities policies for presenting sustainable development, most notably in footings of waste minimisation, H2O efficiency, community regeneration and societal inclusion. In that sense, Private Finance Initiative ( PFI ) as an advanced procurance path can play a cardinal function within the industry due to the graduated table of investing involved ; the greater easiness of act uponing the little figure of histrions involved ; and the manner in which PFI contracts secure the long-run battle of contractors. However, sustainability considerations are non sufficiently embedded in the PFI procedure to guarantee consistent bringing, and success is extremely reliant on the motive and expertness of single public sector clients and private contractors ( Green Alliance ( 2004 ) ) . Sustainability within the building industry has no clearly settled definition and no settled organic structure of bing pattern and procedures. The industry has to understand what sustainability is in its context and concentrate on creative activity, prolonging and airing of cognition for sustainable building across the multiple interest holders involved in building undertakings ( Shelbourn et al. , 2006 ) . Many building companies in the UK follow the authorities ‘s aim for sustainable development which is economic growing and prosperity, effectual protection of the environment, careful usage of natural resources ( natural resource protection and environmental sweetening ) and societal advancement. The UK authorities has produced enterprises to title-holder sustainability within the building industry to accomplish sustainable development marks. Recent research plans such as ‘Partners in Innovation ( PiI ) ‘ ( Shelbourn et al, ( 2006 ) ) and others have been funded to back up sustainability within the building industry ( Raynsford ( 2000 ) ) . The ‘Government Construction Clients Panel ‘ ( dwelling of representatives with duty for procurance for most authorities organic structures ) besides has a mark to accomplish sustainability in each undertaking. This enables the authorities to take a prima function, and showcase good pattern in advancing sustainable building ( DEFRA, ( 2004 ) ) . It is the writers ‘ contention that, every company in the building concern must hold a sustainability policy which will be developed and communicated within the organisation. Those policies can be Sustainability Policy, Environmental Policy, Health and Safety Policy and Sustainable Procurement Policy. The policy and rules of sustainability creates a sustainable development which is supported by a sound sustainability scheme. The purpose of such schemes is to develop a common apprehension of the sustainability issues and present effectual and targeted attacks for each stakeholder to lend to accomplishing a more sustainable building industry. In order to recognize all these policies and scheme it is perfectly necessary to hold a Board and Advisory Committee within the organisation that supports and commits to sustainability as a scheme and acts as a nexus between office and operational activities at site degree. Having set these marks fiting with the Government ‘s sustainab le development, building houses must put specific one-year marks for each concern unit and each building undertaking as a whole. After that each house must besides put for his undertakings and company a sustainability appraisal standard which is linked to marks and Key Performance Indicators ( KPI ‘s ) aligned with the concern scheme of the house. These are meant to be some sporadic thoughts from the writers to the building houses that are likely to follow in execution of Sustainability Policy and Strategy in their organisations. The experiences from some taking UK building companies have shown that there are strong concern benefits for more sustainable building. As a successful instance â€Å" Early Solutions Together – Eastern time † programme of Morgan-Est ( Part of Morgan Sindall ) and â€Å" Making Tomorrow a Better Topographic point † programme of Carillion can be named as two good illustrations of sustainable thought and execution in the UK building industry ( Morgan-Est, 2009 ; Carillion, 2009 ) . Carillion is winner of its category – Best Green Company in the UK for medium to big houses Awards in 2008 and Morgan-Est is the victor of Green Apple Award for Environmental Best Practice. This is besides demonstrated through research carried out by Sustainable Construction Task Group ( BRE ( 2001 ) , which concluded that there are clear advantages to be gained, but merely if sustainability is portion of a long-run concern program. This is reinforced by the Building Research Esta blishment, where research has concluded that â€Å" aˆÂ ¦being sustainable is every bit much about efficient profit-orientated pattern and value for money as it is about assisting the environmentaˆÂ ¦ † ( BRE Report ( 2002 ) ) . Such consequences have given the building industry an improved consciousness of sustainability issues. In 1999, around 150 quality of life indexs were produced to better the wellbeing of UK citizens ( Audit Commission ( 2002 ) ) . The industry has begun to acknowledge that monitoring and coverage on sustainability is a critical portion of their concern. Cardinal Performance Indicators, Environmental Performance Indicators, and the acceptance of benchmarking have become progressively common topographic point, and many companies are now bring forthing environmental and sustainability studies, with corporate societal duty going common pattern ( Movement for Innovation, ( 2000 ) , CIRIA ( 2001, 2006 ) . Sing building in developing states, Ofori ( 2007 ) states that, an organized action should be taken to guarantee that the high volume of building that will be undertaken in the development states in the procedure of urbanisation in the ways that are socially and ecologically impact of building. He stresses that this will necessitate a wide duologue between authoritiess, building industry, academe and NGO ‘s at national and international degrees towards the development and execution programs for sustainable building. 4. Turkish building services bunch Harmonizing to Katsarakis et Al ( 2007 ) , the building services bunch in Turkey is the thirteenth largest in footings of exports and has demonstrated a compound one-year growing rate ( CAGR ) of 63 % for the period of 2002 – 2006 in international projects. While the building services bunch represents merely the 6 % of Turkey ‘s gross domestic merchandise ( GDP ) , together with all complementary and related industries, it still accounts for 30 % of GDP harmonizing to the TCA ( 2009 ) records. Construction plays a important function in Turkey ‘s economic system using about 1.4 million people which is about 5.5 % of Turkey ‘s entire employment. Turkish building sector is chiefly composed of Small and Medium Enterprises. This composing is really similar to the European building sector. The building sector is chiefly a domestic sector and merely 4 % is international building. The European building industry excessively is composed of about 97 % of SME ‘s. The bunch is divided into two groups: the lower-quality domestic-only set of houses and the higher choice international houses by Katsarakis et Al ( 2007 ) . These two groups portion some but non all bunch participants. On the domestic side, there are more than 30,000 active local houses. On the international side, there are over 140 houses registered to the Turkish Contractors Association, 23 of which are among the 225 largest building companies worldwide in footings of abroad activities ( ENR, Engineering News records ( 2008 ) ) . Harmonizing to a study on the web site of TCA about the Turkish Contracting in the International Market, â€Å" in the last 36 old ages, u p until the terminal of 2008, Turkish Contractors have undertaken about 5,000 undertakings in 70 states, with a combined value of some 130 billion USD. Turkey ranks among the top 12 manufacturers of edifice stuffs in the universe, with such merchandises as cement, glass, steel and ceramic tiles taking a prima function. † Further detailed information is provided in a publication by Yapi Endustri Merkezi ( 2007 ) as follows sing the services of the building and the related industries, Turkey is the 11th largest manufacturer of steel in the universe and third-largest in Europe. Turkey ranks 6th in Europe and 15th in the universe in the production of articles of steel. Turkey is the universe ‘s richest state in marble, with a 40 per centum portion of entire planetary militias. Turkey is the universe ‘s 5th and 4th largest manufacturer of ceramic tiles and ceramic healthful ware, severally. Turkey is among the top glass makers of the universe. Turkey is the 6th largest manufacturer of pigments in Europe. Turkey is the 3rd largest manufacturer of plastic doors and Windowss in Europe. There are 200 major technology confer withing companies in Turkey which are supplying 65 % of the proficient consultancy services realized in Turkey and 90 % of the consultancy services required by the Turkish houses abroad, harmonizing to the records of Association of Turkish Consulting Engineers and Architects ( ATCEA ) presented at their web site. Their one-year turnover is about $ 350 million, and they employ about 5,000 people. 5. Turkey ‘s place on sustainable development Business involvement in corporate sustainability is turning in Turkey. Nemli ( 2009 ) investigated taking Turkish companies ‘ attack to corporate sustainability regarding, Their attitudes and attacks toward sustainability, Their chief patterns associating to environmental and societal sustainability, The grounds why companies adopted sustainability patterns, The grounds why companies have non adopted sustainability patterns and Which companies produce environmental, societal or sustainability studies. Nemli ‘s pre-research surveies showed that merely a few of these companies had formal sustainability schemes. Therefore an scrutiny of the sustainability patterns of these few companies would be more enlightening about sustainability in Turkey. The fact that there are so few companies prosecuting sustainability schemes in Turkey indicates that Turkish companies are at the beginning of sustainability execution in their concern. Nemli ‘s research was related to the fabrication companies and none of the examined companies was involved in the building sector. Harmonizing to Turkey ‘s National Report on Sustainable Development by Ministry of Environment ( 2002 ) and besides summarized in a survey made by Ozkan ( 2003 ) , most of the environmental statute law in Turkey has been affected during the past decennary. An overall appraisal of the Turkish environmental statute law indicates that during the past two old ages, the construct of sustainability was clearly included in the Torahs and ordinances put into consequence. The undermentioned ordinances are considered to be vitally of import, Environmental Impact Assessment Regulations, Solid Waste Control Regulations, Hazardous Waste Control Regulations, Air Quality Control Regulations, Water Pollution Control Regulations, Waste Control Regulations, Hazardous Waste Control Regulations. Furthermore, the Ministry of Environment is taking farther legal steps to forestall and command environmental pollution. In this respect, the bing statute law is being reviewed as portion of the attempts to harmonise them with EU statute law. It is anticipated that this measure will lend well towards accomplishing the ends for sustainable development. Turkey had been prosecuting policies in the countries of energy efficiency and environmentally sound engineerings, every bit good as industrial pollution control.A To accomplish sustainable energy development and energy efficiency, the Government had been beef uping attempts to develop and utilize safe engineerings, advancing research and development for appropriate methodological analysiss, raising public consciousness of the issues, and measuring environmental impacts ( A °lkin ( 2006 ) ) .A Harmonizing to the National Report on Sustainable Development 2002, during the past few old ages at that place has been an addition in industrial preparation plans related to work safety, environmental direction systems, quality confidence, and in-service preparation. These plans have been initiated by the Union of Chambers of Commerce and Industry, stock exchanges, Small and Medium Industry Development Organization ( KOSGEB ) , the Quality Association ( KALDER ) , universities, and research establishments ( Ozkan, ( 2003 ) ) . Recycling of edifice stuffs is a really new construct in Turkey. It is merely after the lay waste toing temblor of 1999 in the Marmara part, that some attending has been paid to the huge sum of constructing dust accumulated from the collapsed and dismantled edifices. Waste recycling is recommended and encouraged by the Turkish Ministry of Environment ( Ozkan, ( 2003 ) ) . The Regulations for solid waste disposal go so far as to order that recycled stuffs should be preferred to new 1s. However, the waste referred to in the ordinances belongs to industrial procedures or boxing merely. Harmonizing to the National Report on Sustainability, â€Å" Waste direction is one of the major constituents of the execution of the sustainability rules. Industrial waste direction requires that wastes caused by industry, production and services be managed for the protection of environmental and human wellness by cut downing the loss of natural stuffs used in fabrication. Reducing the sum of waste at the beginning, waste recovery and recycling, every bit good as implementing appropriate waste disposal techniques are among the basic constituents of sustainable development. † ( Ministry of Environment, 2002 ) Harmonizing to Turkey ‘s National Report on Sustainable Development ( 2002 ) , the type of industrial waste in Turkey as a underdeveloped state, is non much different from the type of waste encountered in the developed states of the universe. In order to quantify the sum and composing of industrial waste and to look into the attendant environmental jobs caused Turkish Statistical Institute ( TUIK ) and assorted local authoritiess and industrial organisations ( Union of Chambers of Commerce, Industry, Maritime Trade and Commodity Exchanges of Turkey, Chambers of Industry of Istanbul and Kocaeli ) have conducted independent surveies to develop industrial waste stock lists for the period of 1991-1995. Although the industrial waste stock lists of the fabrication sector for 1994-1997, prepared by the TUIK, did non cover the full state, it is the lone legitimate waste stock list informations bank that exists in Turkey. Besides the Industrial Waste Statistics of TUIK, the Ministry of Environment has besides concluded a elaborate industrial waste stock list undertaking in 2002, which encompasses the Marmara, the Mediterranean, and the Western Anatolia Regions ( Ozkan, 2003 ) . Waste generated by the building industry has non been accounted for in the statistics for industrial or family wastes. Since information for waste produced or disposed by the building industry has non been collected by any of these bureaus, the impact of waste from building industries is besides non known. Esin and Cosgun ( 2007 ) argue that retrieving of building waste is non yet prevailing in Turkey. The primary environmental concern should be the prevention/reduction of the coevals of building waste. Sing the sum of waste generated, Turkey declared in the 9th Five Year Development Plan that the primary mark for commanding solid waste is the decrease of the sum of waste generated ( State Planning Organization ( SPO ) , ( 2006 ) ) . One of the basic rules of the said Development Plan is â€Å" Natural resources, cultural assets and the environment will be protected sing the hereafter coevalss, every bit good † . The study furthermore underscores the Turkish State ‘s decision and will sing the sustainability in resource use in following diction: â€Å" Rapid population growing and industrialisation continue to be of import factors endangering sustainable usage of natural resources. The uncertainnesss about the responsibility and authorization distribution among establishments, for the sustainable usage of natural resources while protecting the environment without adversely impacting the production procedure, could non be adequately eliminated ( Item 159, p.38 ) † and â€Å" More efficient production and less waste will be achieved by increasing the effectivity in natural stuff usage with the execution of environment friendly techniques in industry ( Item 463, p.87 ) † . 6. Discussion Turkey has a strong building sector which can easy be considered as a regional leader in quality building and building stuffs. From the literature study it is evident that Turkey ‘s building industry ‘s sustainability place is non to the full structured yet. A few writers indicate that Turkish companies are at the beginning of implementing policies for sustainability. A study done by Turk ( 2009 ) studies that out 68 companies which are members of TCA surveyed had revealed that merely 28 of them had ISO-14001 enfranchisement. The prevailing governmental sustainability papers in Turkey is dated to 2002. Sustainability is a path that all building industries must travel through. This necessitates the industry to alter their concern scheme and organisational constructions and civilizations. This is a long-run and uninterrupted procedure that needs alteration and version of the sustainability attack to make competitory advantage over other challengers in the industry. Global challenges associated with sustainable development are multifaceted, affecting economic, societal, and environmental concerns. These challenges have deductions for virtually every facet of a building house ‘s scheme and concern theoretical account. Most directors frame sustainable development non as a multidimensional chance, but instead as a unidimensional job, affecting ordinances, added cost, and liability. The jobs of stuff ingestion, waste, and pollution associated with industrialisation nowadays an chance for houses to lower cost through the development of accomplishments and capablenesss in pollution bar and eco-efficiency. Investings made to protect the environment or as portion of societal duty were seen as investings that increase the overall costs and diminish fiscal return. Clean engineerings are normally more efficient therefore cut downing emanations and increasing productiveness. Reducing natural stuff usage and increasing recycling and recovery can cut down production costs. There are chances for cost nest eggs that may non go evident even though the benefits accrue straight to the company, until the company is motivated either by ordinance or concerns to better sustainability public presentation to analyze ways of turn toing these jobs and to put in the necessary research ( Nemli, ( 2009 ) ) . The companies ‘ committedness to corporate societal duty and overall repute may be an of import motivation factor for its current and prospective employees. There is besides an insurance value associated with repute. In the event of a job, a company with a good repute can bring on more supportive responses from stakeholders. Output extends beyond organisational boundaries to include the full merchandise life cycle-from natural stuff entree, through production procedures, to merchandise usage and disposal of spent merchandises. Output therefore involves incorporating the desire of the stakeholder into concern procedures through extended interaction with external parties such as providers, clients, regulators, communities, non-governmental organisations, and the media. As such, it offers a manner to both lower environmental impacts across the value concatenation and enhance legitimacy and repute by affecting stakeholders in the behavior of ongoing operations. ( Hart et Al ( 2003 ) ) . The industry and the disposal have to develop a macro policy which will incorporate societal, economical and environmental policies needed to accomplish a sustainable development of the Turkish building industry as a whole. A holistic sustainability policy covering the full building bunch does non be in Turkey yet. The industry needs to make a political organizational organic structure which is compatible with the demands of sustainable development and which is compatible with similar organisations across the universe. For case, The UK Government ‘s scheme for more sustainable building ( DETR, 2000 ) suggests cardinal factors for action by the building industry by widening the basic subjects. These include design for minimal waste ; thin building ; minimise energy in building and usage ; make non foul ; preserve and enhance biodiversity ; conserve H2O resources ; respect people and local environment ; and put marks, proctor and study, in order to benchmark public presentation ( Raynsford ( 2000 ) , Langston & A ; Ding ( 2001 ) , Miyatake ( 1996 ) ) . These could every bit use to Turkey. Advanced experiments from good illustrations in other states can be adapted to the constitutions of the Turkish building sustainable development attempt. The sector requires more funding to build sustainable undertakings due to the current higher monetary value of stuffs, substructure costs and the land-use ratio. It is expected, nevertheless, that the high cost of sustainable building will worsen in line with a rise in the figure of such undertakings. Many clients and end-users are going witting of the sensitive state of affairs of the environment, and are demoing an increasing penchant for buying sustainable terminal merchandises. For illustration, sustainable lodging reduces operational costs and H2O use, and offers improved security. Meanwhile, lodging investors, though willing to establish nature-sensitive undertakings, are hesitating about the hereafter of the sustainable lodging sector given the high costs associated with it. Sustainable development is one of the most outstanding issues which are emphasized in the Turkey. National Environment Strategy and Action Plan prepared in order to accommodate to the societal and economic state of affairss in Turkey. In the Turkish National Report ( 2002 ) , it is emphasized that in order to sum up the current state of affairs, it has benefited from the Environment subdivision of the 9th Five Year Development Plan ( 2007-2013 ) increased sensitiveness to the demand for a clean environment. Although the environment is a moderately of import issue in Turkey, it has some advantages and disadvantages in respects to environment and sustainable development. The advantages are as stated by TUBITAK ( 2003 ) , Our natural resources ‘ non being wholly polluted, The increasing consciousness of the environment particularly among the immature population, The adequateness of scientific and proficient human resources who can work in this field make it favoured in respects of accomplishing sustainable development. The disadvantages of Turkey in this field are, In malice of non being wholly polluted, their is go oning pollution of natural resources, Making usage of natural resources related to an investing for environmental betterment without taking attention of the set purposes, Not maintaining a record of information and informations consistently related to environment, Data which are recorded holding no criterion in footings of informations aggregation, confirmation, rating and transforming into information. In relation to development programs and sustainable development in Turkish metropoliss, Ercoskun ( 2005 ) argues that the current development programs of metropoliss do non see urban individuality and ecological values and the regional programs do non see infinites between edifices, clime, illuming, way, air circulation, natural energy, etc. , ensuing the Turkish metropoliss to be unsustainable. Furthermore, she states that planning is one of the chief tools in Turkish sustainable development and concluding that the Turkish planning system ( Development Plans, Laws and Applications ) has to be challenged from the sustainability point of position. Supplying sustainable development is non merely limited to direction of natural resources, providing equipment or commanding them. Persons should carry through their responsibilities as responsible citizens in order to accomplish sustainable development with respects of environmental protection. Therefore, it is imperative that persons be taught the topic of sustainable development get downing in primary school, every bit good as doing them cognizant of the environment.

Language Processing and Production Essay

This experiment investigated hemispheric specialisation and dominance with regards to language functions. It used a computer program to measure the amount of key presses achieved by participants in a given time across four different trials (1 with the left hand, no talking, 2 with the left hand whilst being asked questions, and the same two trials again with the right hand). The participants were 2nd year psychology students from which a cohort of 20 was selected for data analysis. A significant difference was found for the effect of hemisphere and language processing task present or absent. However, the means for each trial did not support left hemispheric dominance for language functions: more key presses were recorded when talking and using the right hand than when talking and using the left. Handedness and some involvement of the right hemisphere in language processing and production were also shown as appearing to influence the results obtained. The main conclusion to be drawn is that hemispheric specialisation and language dominance is a subject that needs further investigation in order to clarify the generalisability of conclusions made about left hemisphere language specialisations. Our brain consists of two halves; the left hemisphere and the right hemisphere. The left hemisphere receives information from and controls muscles in the right side of the body, whilst the right hemisphere receives information from and controls muscles in the left side of the body. Research using brain imagery and studies of brain damaged and split brain patients, to name just a few examples, has shown that some of our functions are controlled more by one hemisphere than the other, i.e. are more specialised for that particular function. This experiment aims to investigate these differing specialisations of the hemispheres more deeply and with particular regard to language. Research into language differences between the two hemispheres is widespread and supports the view that the left hemisphere is the more dominant. Marc Dax was the first to notice hemispheric differences in his brain damaged patients, after having seen many patients suffering from loss of speech. Dax found what appeared to be an association between the loss of speech and the side of the brain where the damage occurred. ‘In more than 40 patients with aphasia, Dax noticed damage to the left hemisphere; he was unable to find a case that involved damage to the right hemisphere alone’ (Springer and Deutsch, 1998, p. 1-2). By 1870 further evidence also began to surface, when other investigators began to realise that ‘many types of language disorders could result from damage to the left hemisphere’ (Springer & Deutsch, 1998, p. 1). For example, Broca’s and Wernicke’s aphasia: Broca’s aphasia causes speech problems associated with comprehension, resulting from damage to Broca’s area (situated in the left frontal cortex), whilst Wernicke’s aphasia causes word salad (hard to understand, jumbled speech), resulting from damage to Wernicke’s area (situated in the left temporal lobe). Later research has also supported Dax’s original findings, one example of such research concluded ‘that the left hemisphere is responsible for language in almost all right-handed individuals’ (Butler, S. R. 1997, p. 187). This research also links the additional factor of handedness to investigations of hemispheric lateralisation, an idea which has been supported by others in the field. For example: ‘In right handers †¦ , it is almost always the case that the hemisphere that controls the dominant hand is also the hemisphere that controls speech’ (Springer and Deutsch, 1998, p. 2), therefore it is possible that for left handers, as their dominant hand is being controlled by the right hemisphere, the right hemisphere may be responsible for speech control and other language functions instead of the left hemisphere. Additional research looking at right hemisphere lesions has demonstrated that the right hemisphere is responsible for some linguistical functions: finding that patients with such lesions may be ‘impaired relative to normal controls on certain tests of language’ (Corballis, C. M. 1983, p. 33). One study by Lesser (1974) reported such an impairment ‘on a semantic test involving comprehension of spoken words but not on a phonological or syntactic test’ (Corballis, C. M. 1983, p. 33), suggesting a small role for the right hemisphere in language processing. Kinsbourne and McMurray carried out valuable research using healthy participants, using a procedure similar to the current study (cited in Kalat, 2004, pg. 427). They asked participants to tap with a pencil on a piece of paper as many times as they could in one minute, first with their right hand then with their left, then asked them to do the same again whilst talking, they found that ‘for most right-handers, talking decreases the tapping rate with the right hand more than with the left hand’. This further supports left hemispheric dominance for language, as well as supporting the current study’s methodology and informing its hypothesis. As has been demonstrated most research supports left hemispheric dominance of language functions, but also links hemispheric specialisation with other factors and accepts that the right hemisphere holds some language comprehension control. This experiment looks for further supportive evidence and also briefly looks at handedness as a possible affecting factor. The study uses a finger tapping and language processing task, with the notion that the speed at which keys are pressed will be relatively similar with both hands. If however, if it is the case that language is more associated with the left hemisphere, then on average when processing language, the speed of the right hand will be slower than the left hand, presumably because the left hemisphere then has to do two tasks at once (right hand finger tapping and language processing). This is only the case however if all participants in the experiment have left hemisphere dominance for language, and is thus the reason we have recorded the handedness of our participants. As a result of previous studies and research the hypothesis for this experiment is: there will be differences in the number of taps made from each of the two hands when language is or isn’t being processed. Method Design The experiment used a fully repeated measures within-subjects design: all participants took part in all conditions. There was one independent variable, consisting of four different levels: left hand, talking, no talking and right hand talking, no talking. The dependent variable was the number of key presses made within the time limit of 30 seconds per trial.

Literature review Essay Example | Topics and Well Written Essays - 1500 words

Literature review - Essay Example A study of empirical literature has been carried out with the example of retail industry and considering Wal-Mart as the multinational organization with its operation in several countries being examined under the review. Issues for Multi-national Organisations The various issues for the multinational organization with the example of Wal-Mart as a major player in the retail industry have been discussed below. Strategies of the organization The multinational companies operate in various countries either by establishing its own facilities or with the help of joint ventures. These multinational organizations are thus exposed to country risk of various countries (Butler, 1993, p.58). Wal-Mart, for example Wal-Mart operates around 8500 stores in around 15 countries all over the world and function under 55 different names in several countries. ... Thus the organizational strategies and decision making with respect to these issues are important as the multinational entity would need to take decision of selling the ventures that are not deemed to be profitable in future times. The multinational organization also needs to strategically invest in ventures that would prove to be profitable in future (Jolly, 2003, p.62). These strategic decisions need to consider the issues related to country risk which entails an examination of the political, economic, social, technological and legal environment in the region of investment. Marketing issues The marketing issues, the developments of the various local markets are important areas of consideration for the multinational corporations. The age of globalization has witnessed several new entrants in the local markets and the threat posed by the competitors raise concerns for the multinational companies for retaining their market share. Thus the multinational companies should continuously up date their marketing strategies in order to counter the steps of the competitors for holding their market share in various countries (Solberg, 2002, p.50). Wal-Mart for example being the largest grocery retailer and having presence in around 15 countries are required to anticipate the changing market conditions and demands of the consumers in order to retain their leadership position in the retail industry. Although, the market share of Wal-Mart is three times that of its nearest competitor, Carrefour, the multinational company needs to continuously adopt innovating strategies and respond to the changing lifestyle of the consumers which are market specific for different countries. The multinational companies also

Analyzing a key business leader Essay Example | Topics and Well Written Essays - 1250 words

Analyzing a key business leader - Essay Example Leadership plays a key role in the success of any business and can determine the success or failure of a business venture. Around the world, there are many notable leaders who have managed to steer their companies from small local enterprises to large multinational companies. Richard Branson is one such notable leader. An article entitled The importance of being Richard Branson (Knowledge@Wharton 1-3) reveals that Branson is the founder and owner of the Virgin Group – an empire of 350 companies with ventures in the airline, telecommunication, trains, cosmetic, credit card and several other industries. His empire is worth over 7 billion dollars and it employs over 9,000 people in 28 countries (Morris, par. He has also been recognized as one the 25 most influential leaders in the last 25 years. He is a leader who has mastered the ability to build successful brands and the ability to create a common purpose among his followers. At the core of Branson’s leadership style, is his belief that people, or more specifically his employees, are the foundation of his company success. A Wall Street Journal poll carried out in 2004 reported the following five characteristics as strengths that make a good leader; integrity, ability to get along with others, industriousness, intelligence, business knowledge and education (Ebersohn, 11). Branson’s integrity is perhaps best exemplified by his open and honest attitude to his employees. He believes that it is important that employees are aware at all times about the successes and the problems that the company is going through. He encourages the celebration of company successes and on the other hand also encourages his employees to suggest solutions and innovation to grow the company and solve any problems the company might be going through. Branson is known as a hard worker. His industriousness nature is often described as workaholic. His intelligence is manifested in his ability to identify good business

Colorado Water Supply to California Essay Example | Topics and Well Written Essays - 1000 words

Colorado Water Supply to California - Essay Example This water is around 95 million acre feet and while most of it is absorbed by the forests and rangelands, some 16 MAF goes into rivers and creeks from where it is supplied to 4.6 million people in Colorado alone. Colorado has a legal obligation to serve other states and thus 8.8 MAF of water goes to south western states including Utah, Nevada, California, New Mexico, Arizona, and Mexico. Even though California is dependent on Colorado for water supply, it needs to understand that water resources of the state are limited and droughts are common in Colorado causing even faster absorption of water. Colorado finds it increasing hard to serve a state as big as California and there are concerns about possible water shortage. California is a huge state and in order for Colorado to supply water, it needs to extract additional 6 MAF of water from reservoirs and storage systems. This has largely had a huge burden on Colorado's water system and during some heavy droughts, its agriculture, recreation, municipalities, and the environment suffered a serious blow. But Colorado is legally obligated to supply water to California due to several interstate compacts, international treaties, and court ordered apportionment. While the state is suffering because of heavy demand of water and not adequate supply, it has managed to somehow been the main supplier for decades. However this will increasingly become difficult as Colorado's population increases. Colorado's population is expected to increase by another 2.8 million by 2030. And this would mean greater demand for water. Colorado would then need an additional 630,000 AF of water supplies to meet its new obligations. Colorado is working on different plans to increase its water supply. Some of these include planning for new reservoirs and dams, expanding existing storage systems and conservation. Summers also place an additional burden on Colorado's water supply. As summer arrives, not only the demand for water increases, the supply also shrinks due to evaporation and heat. This puts Colorado in a precarious situation. We need to understand that while many neighboring states depend on Colorado water, the supply is still not enough and these demands are placing a huge burden on Colorado's capacity to generate water. 1 ("Colorado wrestles", 2007) California needs to exploit other ways in which in can meet the water demands of its people. Placing excess burden on one state is highly dangerous for the health of the state and its people. California has also been warned to limit its dependence on and use of Colorado water. The state is currently drawing much more water than it has been allotted but promises to reduce its dependence by 2015. In a news article, it was reported that, "Dubbed the "4.4 Plan," it lets California receive surplus Colorado River water that would otherwise go to the other states, in return for California's pledge to reduce reliance on the river within 15 years. California is entitled to 4.4 million acre feet of water a year under the 1928 Boulder Canyon Project Act. That agreement was upheld by the U.S. Supreme Court in 1964. Nevada is allotted 300,000 acre feet. Arizona gets 2.8 million acre feet. An acre foot of water is about 326,000 gallons, or roughly the amount needed for an average family of five fo r one year. In recent years, California's annual draw has grown to as much as 800,000 acre feet above its allotment."2

Sarbanes-Oxley Research Paper Example | Topics and Well Written Essays - 750 words

Sarbanes-Oxley - Research Paper Example Oxley. The scenario that led to the implementation of this act was the number of corporate accounting ignominies including that of Enron, Tyco International, Adelphia, Peregrine Systems, and WorldCom etc. According to the US government record, the definitions including ‘Appropriate State Regularity Authority’, ‘Audit’, ‘Audit Committee’, ‘Audit Report’, ‘Board’, ‘Commission’, ‘Issuer’, ‘Non-Audit Services’, ‘Person Associated With a Public Accounting Firm’, ‘Professional Standards’, ‘Public Accounting Firm’, ‘Security’ and ‘State’ shall apply to this act (Public Law 107-204, 2002). It consist of11 sections which is constituted by provisions from additional corporate board responsibilities to criminal penalties and provides for the Securities and Exchange Commission to oversee the implementation of the law. The need of ensuring the existence of an ethical workplace is not only to implement a moral conduct within the firm but also to procure whatever advantage that the firm may achieve when there is a belief among the potential consumers and employees that the company is ethical. Creation and gradual implementation of a proper code of conduct is a method that is commonly adopted by managers to ensure an ethical workplace. ... The Securities and Exchange Commission which was supposed to implement the act created a new agency called Public Company Accounting Oversight Board to review matters regarding accounts of all public companies (cited in The University of Cincinnati College of Law, 2002). The sole intention of the act was to prevent fraud and scandals within the corporate so that the nation’s security markets and economy remain strong. Corporate are entitled to submit clear and accurate financial reports and it defines the interaction between external auditors and audit committees. There are severe penalties and punishments if a violation of the law is detected. As Kuschnik (2008) points out, the section 302 of the act provides that CEO and CFO of the companies must certify and approve the authenticity of the financial reports of their company. Planning is the key part of making the data of the company compatible with the law. It is significant for taking future steps freely and to discuss the project with the auditors and the audit committee. The planning phase is where varying opinions can be put into consideration and a commonly accepted resolution can be formulated. Planning can be executed in a sequential pattern. Staffing has to be done in order to carry out the compliance process. The task should be divided into portions that can be completed in a limited time framework. Selection of a recognized framework for testing and business systems and procedures also prove to be cogent. Examine risk-tolerance and impacts of a possible control failure on an organizational level. Complete outsourcing, co-sourcing, direct lining or utilizing existing staff can be used to completing the process. The key advancement that resulted from the act was enhanced investor confidence and more

Cheap airline services Essay Example | Topics and Well Written Essays - 4000 words

Cheap airline services - Essay Example Cheap airline services generally imply long haul carriers that offer cheaper terms of travel as compared to the average conventional flights. The basic approach has often involved the elimination of certain luxuries, comforts, and services normally associated with luxury airlines. Other approaches involve the introduction of complex methods of determining the cost of travel (Bisignani, 2006, p 45). Some of the problematic issues that attend to the introduction of the cheap airline services involve claims of hidden charges, concerns over the levels of safety and matters of comfort for these airline services. Further, in the liberalized market economy, a flight that is regarded as budget within one region may qualify as expensive in another. This is because there are no structural universal regulatory mechanisms in the global airline business, which could be relied upon for an objective and all-inclusive interpretation of the essential meaning of cheap airline services. Introduction The desire to make airline services affordable and accessible continues to attract various approaches and strategies among different companies spread in different countries across different periods. Studies show that the emergent of the low cost carriers from the mid-1990s led to significant changes in the airline industry particularly within the United States and Europe (Chandler, 2002, p. 4). The idea of cheap airline services often implies a wide range of meanings within different contexts. Although the general idea of offering cheap airline services has some universal connotations, the various strategies employed towards this objective illustrate a highly localized application of the same in terms of the strategies, methods., and the relative levels of success for companies that have attempted to engage in this kind of business (McCartney, 11). Some of the common characteristics of cheap airline services include reduced fare, point-to-point airline services, lack of seat assignme nt, secondary airports flights, lack of free meals or drinks, higher flights frequency, and short flights. These characteristics are usually conducted in various ways depending on the airline’s chosen operational strategy. The terms â€Å"cheap airline services† is often used interchangeably with various other terms that carry the same meaning. Other attendant synonyms include low-cost carriers, budget carriers, no-frills, cheap flights, and discount flights (Flouris & Walker, 2005). Regardless of the different adjectives, the baseline often implies the provision of airline services that cost significantly lower than the average carrier. Generally, cheap airline services are usually conducted in ways that show high levels of efficiency in terms of time and costs. The increased levels of efficiency are important to substitute on some of the areas affected by reduced fares. On this score, it becomes necessary to consider the fact that some of the issues explored in this study are basically aimed at exploring the kind of structures that underpin matters of strategy and revenue with regard to the low cost carriers. Literature Review Multiple studies have attempted to explore the manner in which the low-cost carriers have affected the global airline industry. Academic inquiries have attempted to explore the different kinds of strategies employed by companies that entered the budget airline sector. Studies show that various strategies have been followed by a mixture of results by different countries and across different times (Mentzer, 2000, p. 34). Generally, the literature shows that

Bank management report Essay Example | Topics and Well Written Essays - 2500 words

Bank management report - Essay Example This requires a combined effort on the part of the organization as well as the individual employee to ensure a fit with the job responsibilities and work profile with the career goals of an individual. The present study would highlight the aspect of occupational analysis to ensure job fit and organizational excellence. Analysis of Occupation Business organizations need to include aspects of labour demand and supply in addition to determining price and output if they want to maintain sustainability of their businesses in the prevailing competitive business environment. The labour demand curve which highlights the marginal productivity of labour as a constant function of the labour quantity is largely determined by the price of output and changes in technology. The supply of labour is largely based on the premise that humans largely tend to make a trade off between leisure and work. They largely assume that work is not enjoyable and work is not enjoyable. However they also realise that leisure normally requires a cost for the individuals. It is widely assumed that an hour of leisure requires a person to sacrifice an hour of wage (University at Albany, 2008, p.1). Figure 1: Labour Demand and Supply Curve (Source: Cuthbertson & Gripaio, 1993, p.7) The figure above shows a typical labour demand and supply curve in a perfect economic scenario. However the equilibrium between demand and supply can be shifted due to change in the individual’s perception towards work. For example previously women were largely discouraged from working which reduced the total supply of labour however with changing times women have become an integral part of the labour force causing the number of workers to increase thereby causing a shift in the supply curve. Alternative work opportunity including immigration also play a role in the shifting of the equilibrium between labour demand and supply as attractive markets outside home would cause a shift in the supply curve to the left (Un iversity at Albany, 2008, p.1-2). Human Capital Human capital or the labour force is largely affected by the aspect of wages. The marginal theory of productivity states that under purely competitive market conditions the wage rate is largely constant and hence a firm has the opportunity to decide on the total number of workers to be hired thus determining the market demand for labour on their own. The element of additional or marginal worker largely helps in determining marginal productivity (Chakravarty, 2009, p.600). Employees also have a propensity to go in for higher studies or look for alternative work options. In both these cases the labour supply reduces and the equilibrium wage price gets increased owning to greater propensity and increased marginal wages of the employees in lieu of their higher education or attractive wages in other organizations. Higher education options among the workers would largely tend to shift the labour demand curve to the rightward direction ensuri ng a shift in the equilibrium point between labour demand and supply (Hubbard & O’Brien, 2008, p.504). Labour Migration In a market characterised by elements of perfect market competition labour

New Gay Visibility on TV Article Example | Topics and Well Written Essays - 500 words

New Gay Visibility on TV - Article Example Since there are several television shows that had been focused on stereotyping the same sex relationship, public acceptance of homosexuality becomes a reality. Before 1990, the existence of debate regarding the moral and social issues of homosexuality was controversial topic. Since a lot of heterosexual relationships failed to work, same sex relationships started to become a normal behavior in the United States. Among the well-known television shows that heavily promotes same sex relationship is the 'sex and the city' wherein Samantha who portrayed a character who is willing to experiment on sex including the idea of having sex with a female partner. On the other hand, the show 'Queer as Folks' has been focused on uncovering what it is like living in a gay (men) community whereas 'the L world' unfolds the lesbians. Up to the present, the media is still being used to stereotype homosexual issues as something that is publicly accepted. In line with this, the Simpsons continuously promote homosexuality by coming up with 'the Simpsons gay song', 'Homer Simpson's gay dance', and Bart portraying as gay (You Tube b, c, d). The movie 'You Like Dangerous Guys'' also promoted gay relationship (You Tube e).

Summative Assessment for Master of Midwifery Leadership and Essay

Summative Assessment for Master of Midwifery Leadership and Development (topic to be decided) - Essay Example These classical theories do not take into account individual characteristics of each member and each member’s capacity for potential leadership. Newer theories by Taylor and Weber offer more scientific principles and explanations for management and leadership. Through these theories, we can deduce various techniques in leadership. We can also deduce various elements of an effective team. The various elements of an effective team are: a meaningful and clearly defined task; clear team objectives and individual targets; regular meetings; regular feedbacks on individual and team success in achieving objectives; the right balance of people; reflexivity-the ability to reflect on team performance and adapt and change; a good balance of concern for the team task and concern for the team welfare; the experience of full participation; and good leadership. This study aims to establish the student’s comprehension of the subjects and unit topics covered by this course. It also aims to apply the knowledge that the student has learned in an issue related to leadership and management in healthcare. This study aims to apply the different theories on leadership and management which were discussed in the different sessions of this course. Strong leadership and management skills are important tools for members of the health care team. Without effective leadership skills, the implementation of health care services becomes a counterproductive enterprise. In the nursing care process, the nurse is often called on to be a manager, and in some instances, she is also called on to be a leader. Both roles are different from the other. Wywialowski (1993) refers to nursing management as â€Å"the judicious use of resources to achieve identified client goals†. The responsibilities of the nurse manager include directing and controlling. He distinguishes nursing management from leadership by defining the latter as

Approaches to the Analysis of Survey Data Essay Example for Free

Approaches to the Analysis of Survey Data Essay 1. Preparing for the Analysis 1.1 Introduction This guide is concerned with some fundamental ideas of analysis of data from surveys. The discussion is at a statistically simple level; other more sophisticated statistical approaches are outlined in our guide Modern Methods of Analysis. Our aim here is to clarify the ideas that successful data analysts usually need to consider to complete a survey analysis task purposefully. An ill-thought-out analysis process can produce incompatible outputs and many results that never get discussed or used. It can overlook key findings and fail to pull out the subsets of the sample where clear findings are evident. Our brief discussion is intended to assist the research team in working systematically; it is no substitute for clear-sighted and thorough work by researchers. We do not aim to show a totally naà ¯ve analyst exactly how to tackle a particular set of survey data. However, we believe that where readers can undertake basic survey analysis, our recommendations will help and encourage them to do so better. Chapter 1 outlines a series of themes, after an introductory example. Different data types are distinguished in section 1.2. Section 1.3 looks at data structures; simple if there is one type of sampling unit involved, and hierarchical with e.g. communities, households and individuals. In section 1.4 we separate out three stages of survey data handling – exploration, analysis and archiving – which help to define expectations and procedures for different parts of the overall process. We contrast the research objectives of description or estimation (section 1.5), and of comparison  (section 1.6) and what these imply for analysis. Section 1.7 considers when results should be weighted to represent the population – depending on the extent to which a numerical value is or is not central to the interpretation of survey results. In section 1.8 we outline the coding of non-numerical responses. The use of ranked data is discussed in brief in section 1.9. In Chapter 2 we look at the ways in which researchers usually analyse survey data. We focus primarily on tabular methods, for reasons explained in section 2.1. Simple one-way tables are often useful as explained in section 2.2. Cross-tabulations (section 2.3) can take many forms and we need to think which are appropriate. Section 2.4 discusses issues about ‘accuracy’ in relation to two- and multi-way tables. In section 2.5 we briefly discuss what to do when several responses can be selected in response to one question.  © SSC 2001 – Approaches to the Analysis of Survey Data 5 Cross-tabulations can look at many respondents, but only at a small number of questions, and we discuss profiling in section 2.6, cluster analysis in section 2.7, and indicators in sections 2.8 and 2.9. 1.2 Data Types Introductory Example: On a nominal scale the categories recorded, usually counted, are described verbally. The ‘scale’ has no numerical characteristics. If a single oneway table resulting from simple summarisation of nominal (also called categorical) scale data contains frequencies:Christian Hindu Muslim Sikh Other 29 243 117 86 25 there is little that can be done to present exactly the same information in other forms. We could report highest frequency first as opposed to alphabetic order, or reduce the information in some way e.g. if one distinction is of key importance compared to the others:Hindu Non-Hindu 243 257 On the other hand, where there are ordered categories, the sequence makes sense only in one, or in exactly the opposite, order:Excellent Good Moderate Poor Very Bad 29 243 117 86 25 We could reduce the information by combining categories as above, but also we can summarise, somewhat numerically, in various ways. For example, accepting a degree of arbitrariness, we might give scores to the categories:Excellent Good Moderate Poor Very Bad 5 4 3 2 1 and then produce an ‘average score’ – a numerical indicator – for the sample of:29 Ãâ€" 5 + 243 Ãâ€" 4 + 117 Ãâ€" 3 + 86 Ãâ€" 2 + 25 Ãâ€" 1 29 + 243 + 117 + 86 + 25 = 3.33 This is an analogue of the arithmetical calculation we would do if the categories really were numbers e.g. family sizes. 6  © SSC 2001 – Approaches to the Analysis of Survey Data The same average score of 3.33 could arise from differently patterned data e.g. from rather more extreme results:Excellent Good Moderate Poor Very Bad 79 193 117 36 75 Hence, as with any other indicator, this ‘average’ only represents one feature of the data and several summaries will sometimes be needed. A major distinction in statistical methods is between quantitative data and the other categories exemplified above. With quantitative data, the difference between the values from two respondents has a clearly defined and incontrovertible meaning e.g. â€Å"It is 5C ° hotter now than it was at dawn† or â€Å"You have two more children than your sister†. Commonplace statistical methods provide many well-known approaches to such data, and are taught in most courses, so we give them only passing attention here. In this guide we focus primarily on the other types of data, coded in number form but with less clear-cut numerical meaning, as follows. Binary – e.g. yes/no data – can be coded in 1/0 form; while purely categorical or nominal data – e.g. caste or ethnicity – may be coded 1, 2, 3†¦ using numbers that are just arbitrary labels and cannot be added or subtracted. It is also common to have ordered categorical data, where items may be rated Excellent, Good, Poor, Useless, or responses to attitude statements may be Strongly agree, Agree, Neither agree nor disagree, Disagree, Strongly disagree. With ordered categorical data the number labels should form a rational sequence, because they have some numerical meaning e.g. scores of 4, 3, 2, 1 for Excellent through to Useless. Such data supports limited quantitative analysis, and is often referred to by statisticians as ‘qualitative’ – this usage does not imply that the elicitation procedure must satisfy a purist’s restrictive perception of what constitutes qualitative research methodology. 1.3 Data Structure SIMPLE SURVEY DATA STRUCTURE: the data from a single-round survey, analysed with limited reference to other information, can often be thought of as a ‘flat’ rectangular file of numbers, whether the numbers are counts/measurements, or codes, or a mixture. In a structured survey with numbered questions, the flat file has a column for each question, and a row for each respondent, a convention common to almost all standard statistical packages. If the data form a perfect rectangular grid with a number in every cell, analysis is made relatively easy, but there are many reasons why this will not always be the case and flat file data will be incomplete or irregular. Most importantly:-  © SSC 2001 – Approaches to the Analysis of Survey Data 7 †¢ Surveys often involve ‘skip’ questions where sections are missed out if irrelevant e.g. details of spouse’s employment do not exist for the unmarried. These arise legitimately, but imply different subsets of people respond to different questions. ‘Contingent questions’, where not everyone ‘qualifies’ to answer, often lead to inconsistent-seeming results for this reason. If the overall sample size is just adequate, the subset who ‘qualify’ for a particular set of contingent questions may be too small to analyse in the detail required. †¢ If some respondents fail to respond to some questions (item non-response) there will be holes in the rectangle. Non-informative non-response occurs if the data is missing for a reason unrelated to the true answers e.g. the interviewer turned over two pages instead of one! Informative non-response means that the absence of an answer itself tells you something, e.g. you are almost sure that the missing income value will be one of the highest in the community. A little potentially informative non-response may be ignorable, if there is plenty of data. If data are sparse or if informative  non-response is frequent, the analysis should take account of what can be inferred from knowing that there are informative missing values. HIERARCHICAL DATA STRUCTURE: another complexity of survey data structure arises if the data are hierarchical. A common type of hierarchy is where a series of questions is repeated say for each child in the household, and combined with a household questionnaire, and maybe data collected at community level. For analysis, we can create a rectangular flat file, at the ‘child level’, by repeating relevant household information in separate rows for each child. Similarly, we can summarise information for the children in a household, to create a ‘household level’ analysis file. The number of children in the household is usually a desirable part of the summary; this â€Å"post-stratification† variable can be used to produce sub-group analyses at household level separating out households with different numbers of child members. The way the sampling was done can have an effect on interpretation or analysis of a hierarchical study. For example if children were chosen at random, households with more children would have a greater chance of inclusion and a simple average of the household sizes would be biased upwards: it should be corrected for selection probabilities. Hierarchical structure becomes important, and harder to handle, if there are many levels where data are collected e.g. government guidance and allocations of resource, District Development Committee interpretations of the guidance, Village Task Force selections of safety net beneficiaries, then households and individuals whose vulnerabilities and opportunities are affected by targeting decisions taken at higher levels in the hierarchy. In such cases, a relational database reflecting the hierarchical 8  © SSC 2001 – Approaches to the Analysis of Survey Data structure is a much more desirable way than a spreadsheet to define and retain the inter-relationships between levels, and to create many analysis files at different levels. Such issues are described in the guide The Role of a Database Package for Research Projects. Any one of the analysis files   may be used as we discuss below, but any such study will be looking at one facet of the structure, and several analyses will have to be brought together for an overall interpretation. A more sophisticated approach using multi-level modelling, described in our guide on Modern Methods of Analysis, provides a way to look at several levels together. 1.4 Stages of Analysis It is often worth distinguishing the three stages of exploratory analysis, deriving the main findings, and archiving. EXPLORATORY DATA ANALYSIS (EDA) means looking at the data files, maybe even before all the data has been collected and entered, to get an idea of what is there. It can lead to additional data collection if this is seen to be needed, or savings by stopping collecting data when a conclusion is already clear, or existing results prove worthless. It is not assumed that results from EDA are ready for release as study findings. †¢ EDA usually overlaps with data cleaning; it is the stage where anomalies become evident e.g. individually plausible values may lead to a way-out point when combined with other variables on a scatterplot. In an ideal situation, EDA would end with confidence that one has a clean dataset, so that a single version of the main datafiles can be finalised and ‘locked’ and all published analyses derived from a single consistent form of ‘the data’. In practice later stages of analysis often produce additional queries about data values. †¢ Such exploratory analysis will also show up limitations in contingent questions e.g. we might find we don’t have enough currently married women to analyse their income sources separately by district. EDA should include the final reconciliation of analysis ambitions with data limitations. †¢ This phase can allow the form of analysis to be tried out and agreed, developing analysis plans and program code in parallel with the final data collection, data entry and checking. Purposeful EDA allows the subsequent stage of deriving the main findings to be relatively quick, uncontroversial, and well organised. DERIVING THE MAIN FINDINGS: the second stage will  ideally begin with a clear-cut clean version of the data, so that analysis files are consistent with one another, and any inconsistencies, e.g. in numbers included, can be clearly explained. This is the stage we amplify upon, later in this guide. It should generate the summary  © SSC 2001 – Approaches to the Analysis of Survey Data 9 findings, relationships, models, interpretations and narratives, and recommendations that research users will need to begin utilising the results. first Of course one needs to allow time for ‘extra’ but usually inevitable tasks such as:†¢ follow-up work to produce further more detailed findings, e.g. elucidating unexpected results from the pre-planned work. †¢ a change made to the data, each time a previously unsuspected recording or data entry error comes to light. Then it is important to correct the database and all analysis files already created that involve the value to be corrected. This will mean repeating analyses that have already been done using, but not revealing, the erroneous value. If that analysis was done â€Å"by mouse clicking† and with no record of the steps, this can be very tedious. This stage of work is best undertaken using software that can keep a log: it records the analyses in the form of program instructions that can readily and accurately be re-run. ARCHIVING means that data collectors keep, perhaps on CD, all the non-ephemeral material relating to their efforts to acquire information. Obvious components of such a record include:(i) data collection instruments, (ii) raw data, (iii) metadata recording the what, where, when, and other identifiers of all variables, (iv) variable names and their interpretations, and labels corresponding to values of categorical variables, (v) query programs used to extract analysis files from the database, (vi) log files  defining the analyses, and (vii) reports. Often georeferencing information, digital photographs of sites and scans of documentary material are also useful. Participatory village maps, for example, can be kept for reference as digital photographs. Surveys are often complicated endeavours where analysis covers only a fraction of what could be done. Reasons for developing a good management system, of which the archive is part, include:†¢ keeping the research process organised as it progresses; †¢ satisfying the sponsor’s (e.g. DFID’s) contractual requirement that data should be available if required by the funder or by legitimate successor researchers; †¢ permitting a detailed re-analysis to authenticate the findings if they are questioned; †¢ allowing a different breakdown of results e.g. when administrative boundaries are redefined; †¢ linking several studies together, for instance in longer-term analyses carrying baseline data through to impact assessment. 10  © SSC 2001 – Approaches to the Analysis of Survey Data 1.5 Population Description as the Major Objective In the next section we look at the objective of comparing results from sub-groups, but a more basic aim is to estimate a characteristic like the absolute number in a category of proposed beneficiaries, or a relative number such as the prevalence of HIV seropositives. The estimate may be needed to describe a whole population or sections of it. In the basic analyses discussed below, we need to bear in mind both the planned and the achieved sampling structure. Example: Suppose ‘before’ and ‘after’ surveys were each planned to have a 50:50 split of urban and rural respondents. Even if we achieved 50:50 splits, these would need some manipulation if we wanted to generalise the results to represent an actual population split of 70:30 urban:rural. Say we wanted to assess the change from ‘before’ to ‘after’ and the achieved samples were in fact split 55:45 and 45:55. We would have to correct the  results carefully to get a meaningful estimate of change. Samples are often stratified i.e. structured to capture and represent particular segments of the target population. This may be much more sophisticated than the urban/rural split in the previous paragraph. Within-stratum summaries serve to describe and characterise each of these parts individually. If required by the objectives, overall summaries, which put together the strata, need to describe and characterise the whole population. It may be fine to treat the sample as a whole and produce simple, unweighted summaries if (i) we have set out to sample the strata proportionately, (ii) we have achieved this, and (iii) there are no problems due to hierarchical structure. Nonproportionality arises from various quite distinct sources, in particular:†¢ Case A: often sampling is disproportionate across strata by design, e.g. the urban situation is more novel, complex, interesting or accessible, and gets greater coverage than the fraction of the population classed as rural. †¢ Case B : sometimes particular strata are bedevilled with high levels of nonresponse, so that the data are not proportionate to stratum sizes, even when the original plan was that they should be. If we ignore non-proportionality, a simple-minded summary over all cases is not a proper representation of the population in these instances.  The ‘mechanistic’ response to ‘correct’ both the above cases is (1) to produce withinstratum results (tables or whatever), (2) to scale the numbers in them to represent the true population fraction that each stratum comprises, and then (3) to combine the results.  © SSC 2001 – Approaches to the Analysis of Survey Data 11 There is often a problem with doing this in case B, where non-response is an important part of the disproportionality: the reasons why data are missing from particular strata often correspond to real differences in the behaviour of respondents, especially those omitted or under-sampled, e.g. â€Å"We had very good response rates everywhere except in the north. There a high proportion of the population are nomadic, and we largely failed to find them.† Just  scaling up data from settled northerners does not take account of the different lifestyle and livelihood of the missing nomads. If you have largely missed a complete category, it is honest to report partial results making it clear which categories are not covered and why. One common ‘sampling’ problem arises when a substantial part of the target population is unwilling or unable to cooperate, so that the results in effect only represent a limited subset – those who volunteer or agree to take part. Of course the results are biased towards e.g. those who command sufficient resources to afford the time, or e.g. those who habitually take it upon themselves to represent others. We would be suspicious of any study which appeared to have relied on volunteers, but did not look carefully at the limits this imposed on the generalisability of the conclusions. If you have a low response rate from one stratum, but are still prepared to argue that the data are somewhat representative, the situation is at the very least uncomfortable. Where you have disproportionately few responses, the multipliers used in scaling up to ‘represent’ the stratum will be very high, so your limited data will be heavily weighted in the final overall summary. If there is any possible argument that these results are untypical, it is worthwhile to think carefully before giving them extra prominence in this way. 1.6 Comparison as the Major Objective One sound reason for disproportionate sampling is that the main objective is a comparison of subgroups in the population. Even if one of two groups to be compared is very small, say 10% of the total number in the population, we now want roughly equally many observations from each subgroup, to describe both groups roughly equally accurately. There is no point in comparing a very accurate set of results from one group with a very vague, ill-defined description of the other; the comparison is at least as vague as the worse description. The same broad principle applies whether the comparison is a wholly quantitative one looking at the difference in means of a numerical measure between groups, or a much looser verbal comparison e.g. an assessment of differences in pattern across a range of cross-tabulations. 12  © SSC 2001 – Approaches to the Analysis of Survey Data If for a subsidiary objective we produce an overall summary giving ‘the general picture’ of which both groups are part, 50:50 sampling may need to be re-weighted 90:10 to produce a quantitative overall picture of the sampled population. The great difference between true experimental approaches and surveys is that experiments usually involve a relatively specific comparison as the major objective, while surveys much more often do not. Many surveys have multiple objectives, frequently ill defined, often contradictory, and usually not formally prioritised. Along with the likelihood of some non-response, this tends to mean there is no sampling scheme which is best for all parts of the analysis, so various different weighting schemes may be needed in the analysis of a single survey. 1.7 When Weighting Matters Several times in the above we have discussed issues about how survey results may need to be scaled or weighted to allow for, or ‘correct for’, inequalities in how the sample represents the population. Sometimes this is of great importance, sometimes not. A fair evaluation of survey work ought to consider whether an appropriate tradeoff has been achieved between the need for accuracy and the benefits of simplicity. If the objective is formal estimation, e.g. of total population size from a census of a sample of communities, we are concerned to produce a strictly numerical answer, which we would like to be as accurate as circumstances allow. We should then correct as best we can for a distorted representation of the population in the sample. If groups being formally compared run across several population strata, we should try to ensure the comparison is fair by similar corrections, so that the groups are compared on the basis of consistent samples. In these cases we have to face up to problems such as unusually large weights attached to poorly-responding strata, and we may need to investigate the extent to which the final answer is dubious because of sensitivity to results from such subsamples. Survey findings are often used in ‘less numerical’ ways, where it may not be so important to achieve accurate weighting e.g. â€Å"whatever varieties they grow for sale, a large majority of farm households in Sri Lanka prefer traditional red rice varieties for home consumption because they prefer their flavour†. If this is a clear-cut finding which accords with other information, if it is to be used for a simple decision process, or if it is an interim finding which will prompt further investigation, there is a lot to be said for keeping the analysis simple. Of course it saves time and money. It makes the process of interpretation of the findings more accessible to those not very involved in the study. Also, weighting schemes depend on good information to create the weighting factors and this may be hard to pin down.  © SSC 2001 – Approaches to the Analysis of Survey Data 13 Where we have worryingly large weights, attaching to small amounts of doubtful information, it is natural to want to put limits on, or ‘cap’, the high weights, even at the expense of introducing some bias, i.e. to prevent any part of the data having too much impact on the result. The ultimate form of capping is to express doubts about all the data, and to give equal weight to every observation. The rationale, not usually clearly stated, even if analysts are aware they have done this, is to minimise the maximum weight given to any data item. This lends some support to the common practice of analysing survey data as if they were a simple random sample from an unstructured population. For ‘less numerical’ usages, this may not be particularly problematic as far as simple description is concerned. Of course it is wrong – and may be very misleading – to follow this up by calculating standard deviations and making claims of accuracy about the results which their derivation will not sustain! 1.8 Coding We recognise that purely qualitative researchers may prefer to use qualitative analysis methods and software, but where open-form and other verbal responses occur alongside numerical data it is often sensible to use a quantitative tool. From the statistical viewpoint, basic coding implies that we have material, which can be put into nominal-level categories. Usually this is recorded in verbal or pictorial form, maybe on audio- or videotape, or written down by interviewers or self-reported. We would advocate computerising the raw data, so it is archived. The following refers to extracting codes, usually describing the routine comments, rather than unique individual ones which can be used for subsequent qualitative analysis. By scanning the set of responses, themes are developed which reflect the items noted in the material. These should reflect the objectives of the activity. It is not necessary to code rare, irrelevant or uninteresting material. In the code development phase, a large enough range of the responses is scanned to be reasonably sure that commonly occurring themes have been noted. If previous literature, or theory, suggests other themes, these are noted too. Ideally, each theme is broken down into unambiguous, mutually exclusive and exhaustive, categories so that any response segment can be assigned to just one, and assigned the corresponding code value. A ‘codebook’ is then prepared where the categories are listed and codes assigned to them. Codes do not have to be consecutive numbers. It is common to think of codes as presence/absence markers, but there is no intrinsic reason why they should not be graded as ordered categorical variables if appropriate, e.g. on a scale such as fervent, positive, uninterested/no opinion, negative. 14  © SSC 2001 – Approaches to the Analysis of Survey Data The entire body of material is then reviewed and codes are recorded. This may be in relevant places on questionnaires or transcripts. Especially when looking at ‘new’ material not used in code development, extra items may arise and need to be added to the codebook. This may mean another pass through material already reviewed, to add new codes e.g. because a  particular response is turning up more than expected. From the point of view of analysis, no particular significance attaches to particular numbers used as codes, but it is worth bearing in mind that statistical packages are usually excellent at sorting, selecting or flagging, for example, ‘numbers between 10 and 19’ and other arithmetically defined sets. If these all referred to a theme such as ‘forest exploitation activities of male farmers’ they could easily be bundled together. It is of course impossible to separate out items given the same code, so deciding the right level of coding detail is essential at an early stage in the process. When codes are analysed, they can be treated like other nominal or ordered categorical data. The frequencies of different types of response can be counted or cross-tabulated. Since they often derive from text passages and the like, they are often particularly well-adapted for use in sorting listings of verbal comments – into relevant bundles for detailed non-quantitative analysis. 1.9 Ranking Scoring A common means of eliciting data is to ask individuals or groups to rank a set of options. The researchers’ decision to use ranks in the first place means that results are less informative than scoring, especially if respondents are forced to choose between some nearly-equal alternatives and some very different ones. A British 8-year-old offered baked beans on toast, or fish and chips, or chicken burger, or sushi with hot radish might rank these 1, 2, 3, 4 but score them 9, 8.5, 8, and 0.5 on a zero to ten scale! Ranking is an easy task where the set of ranks is not required to contain more than about four or five choices. It is common to ask respondents to rank, say, their best four from a list of ten, with 1 = best, etc. Accepting a degree of arbitrariness, we would usually replace ranks 1, 2, 3, 4, and a string of blanks by pseudo-scores 4, 3, 2, 1, and a string of zeros, which gives a complete array of numbers we can summarise – rather than a sparse array where we don’t know how to handle the blanks. A project output paper†  available on the SSC website explores this in more detail. †  Converting Ranks to Scores for an ad hoc Assessment of Methods of Communication Available to Farmers by Savitri Abeyasekera, Julie  Lawson-Macdowell Ian Wilson. This is an output from DFID-funded work under the Farming Systems Integrated Pest Management Project, Malawi and DFID NRSP project R7033, Methodological Framework for Combining Qualitative and Quantitative Survey Methods.  © SSC 2001 – Approaches to the Analysis of Survey Data 15 Where the instructions were to rank as many as you wish from a fixed, long list, we would tend to replace the variable length lists of ranks with scores. One might develop these as if respondents each had a fixed amount, e.g. 100 beans, to allocate as they saw fit. If four were chosen these might be scored 40, 30, 20, 10, or with five chosen 30, 25, 20, 15, 10, with zeros again for unranked items. These scores are arbitrary e.g. 40, 30, 20, 10 could instead be any number of choices e.g. 34, 28, 22, 16 or 40, 25, 20, 15; this reflects the rather uninformative nature of rankings, and the difficulty of post hoc construction of information that was not elicited effectively in the first place. Having reflected and having replaced ranks by scores we would usually treat these like any other numerical data, with one change of emphasis. Where results might be sensitive to the actual values attributed to ranks, we would stress sensitivity analysis more than with other types of numerical data, e.g. re-running analyses with (4, 3, 2, 1, 0, 0, †¦) pseudo-scores replaced by (6, 4, 2, 1, 0, 0 , †¦). If the interpretations of results are insensitive to such changes, the choice of scores is not critical. 16  © SSC 2001 – Approaches to the Analysis of Survey Data 2. Doing the Analysis 2.1 Approaches Data listings are readily produced by database and many statistical packages. They are generally on a case-by-case basis, so are particularly suitable in  EDA as a means of tracking down odd values, or patterns, to be explored. For example, if material is in verbal form, such a listing can give exactly what every respondent was recorded as saying. Sorting these records – according to who collected them, say – may show up great differences in field workers’ aptitude, awareness or approach. Data listings can be an adjunct to tabulation: in Excel, for example, the Drill Down feature allows one to look at the data from individuals who appear together in a single cell. There is a place for the use of graphical methods, especially for presentational purposes, where simple messages need to be given in easily understood, and attentiongrabbing form. Packages offer many ways of making results bright and colourful, without necessarily conveying more information or a more accurate understanding. A few basic points are covered in the guide on Informative Presentation of Tables, Graphs and Statistics. Where the data are at all voluminous, it is a good idea selectively to tabulate most ‘qualitative’ but numerically coded data i.e. the binary, nominal or ordered categorical types mentioned above. Tables can be very effective in presentations if stripped down to focus on key findings, crisply presented. In longer reports, a carefully crafted, well documented, set of cross-tabulations is usually an essential component of summary and comparative analysis, because of the limitations of approaches which avoid tabulation:†¢ Large numbers of charts and pictures can become expensive, but also repetitive, confusing and difficult to use as a source of detailed information. †¢ With substantial data, a purely narrative full description will be so long-winded and repetitive that readers will have great difficulty getting a clear picture of what the results have to say. With a briefer verbal description, it is difficult not to be overly selective. Then the reader has to question why a great deal went into collecting data that merits little description, and should question the impartiality of the reporting. †¢ At the other extreme, some analysts will skip or skimp the tabulation stage and move rapidly to complex statistical modelling. Their findings are just as much to be distrusted! The models may be based on preconceptions rather than evidence, they may fit badly and conceal important variations in the underlying patterns.  © SSC 2001 – Approaches to the Analysis of Survey Data 17 †¢ In terms of producing final outputs, data listings seldom get more than a place in an appendix. They are usually too extensive to be assimilated by the busy reader, and are unsuitable for presentation purposes. 2.2 One-Way Tables The most straightforward form of analysis, and one that often supplies much of the basic information need, is to tabulate results, question by question, as ‘one-way tables’. Sometimes this can be done using an original questionnaire and writing on it the frequency or number of people who ‘ticked each box’. Of course this does not identify which respondents produced particular combinations of responses, but this is often a first step where a quick and/or simple summary is required. 2.3 Cross-Tabulation: Two-Way Higher-Way Tables At the most basic level, cross-tabulations break down the sample into two-way tables showing the response categories of one question as row headings, those of another question as column headings. If for example each question has five possible answers the table breaks the total sample down into 25 subgroups. If the answers are subdivided e.g. by sex of respondent, there will be one three-way table, 5x5x2, probably shown on the page as separate two-way tables for males and for females. The total sample size is now split over 50 categories and the degree to which the data can sensibly be disaggregated will be constrained by the total number of respondents represented. There are usually many possible two-way tables, and even more three-way tables. The main analysis needs to involve careful thought as to which ones are necessary, and how much detail is needed. Even after deciding that we want some cross-tabulation with categories of ‘question J’ as rows and ‘question K’ as columns, there are several other  decisions to be made: †¢ The number in the cells of the table may be just the frequency i.e. the number of respondents who gave that combination of answers. This may be rephrased as a proportion or a percentage of the total. Alternatively, percentages can be scaled so they total 100% across each row or down each column, so as to make particular comparisons clearer. †¢ The contents of a cell can equally well be a statistic derived from one or more other questions e.g. the proportion of the respondents falling in that cell who were economically-active women. Often such a table has an associated frequency table to show how many responses went in to each cell. If the cell frequencies represent 18  © SSC 2001 – Approaches to the Analysis of Survey Data small subsamples the results can vary wildly, just by chance, and should not be over-interpreted. †¢ Where interest focuses mainly on one ‘area’ of a two-way table it may be possible to combine rows and columns that we don’t need to separate out, e.g. ruling party supporters vs. supporters of all other parties. This simplifies interpretation and presentation, as well as reducing the impact of chance variations where there are very small cell counts. †¢ Frequently we don’t just want the cross-tabulation for ‘all respondents’. We may want to have the same table separately for each region of the country – described as segmentation – or for a particular group on whom we wish to focus such as ‘AIDS orphans’ – described as selection. †¢ Because of varying levels of success in covering a population, the response set may end up being very uneven in its coverage of the target population. Then simply combining over the respondents can mis-represent the intended population. It may be necessary to show the patterns in tables, sub-group by sub-group to convey the whole picture. An alternative, discussed in Part 1, is to weight up the results from the sub-groups to give a fair representation of the whole. 2.4 Tabulation the Assessment of Accuracy Tabulation is usually purely descriptive, with limited effort made to assess the ‘accuracy’ of the numbers tabulated. We caution that confidence intervals are sometimes very wide when survey samples have been disaggregated into various subgroups: if crucial decisions hang on a few numbers it may well be worth putting extra effort into assessing – and discussing – how reliable these are. If the uses intended for various tables are not very numerical or not very crucial, it is likely to cause unjustifiable delay and frustration to attempt to put formal measures of precision on the results. Usually, the most important considerations in assessing the ‘quality’ or ‘value’ or ‘accuracy’ of results are not those relating to ‘statistical sampling variation’, but those which appraise the following factors and their effects:†¢ evenness of coverage of the target (intended) population †¢ suitability of the sampling scheme reviewed in the light of field experience and findings †¢ sophistication and uniformity of response elicitation and accuracy of field recording †¢ efficacy of measures to prevent, compensate for, and understand non-response †¢ quality of data entry, cleaning and metadata recording †¢ selection of appropriate subgroups in analysis  © SSC 2001 – Approaches to the Analysis of Survey Data 19 If any of the above factors raises important concerns, it is necessary to think hard about the interpretation of ‘statistical’ measures of precision such as standard errors. A factor that has uneven effects will introduce biases, whose size and detectability ought to be dispassionately appraised and reported with the conclusions. Inferential statistical procedures can be used to guide generalisations from the sample to the population, where a  survey is not badly affected by any of the above. Inference addresses issues such as whether apparent patterns in the results have come about by chance or can reasonably be taken to reflect real features of the population. Basic ideas are reviewed in Understanding Significance: the Basic Ideas of Inferential Statistics. More advanced approaches are described in Modern Methods of Analysis. Inference is particularly valuable, for instance, in determining the appropriate form of presentation of survey results. Consider an adoption study, which examined socioeconomic factors affecting adoption of a new technology. Households are classified as male or female headed, and the level of education and access to credit of the head is recorded. At its most complicated the total number of households in the sample would be classified by adoption, gender of household head, level of education and access to credit resulting in a 4-way table. Now suppose, from chi-square tests we find no evidence of any relationship between adoption and education or access to credit. In this case the results of the simple twoway table of adoption by gender of household head would probably be appropriate. If on the other hand, access to credit were the main criterion affecting the chance of adoption and if this association varied according to the gender of the household head, the simple two-way table of adoption by gender would no longer be appropriate and a three-way table would be necessary. Inferential procedures thus help in deciding whether presentation of results should be in terms of one-way, two-way or higher dimensional tables. Chi-square tests are limited to examining association in two-way tables, so have to be used in a piecemeal fashion for more complicated situations like that above. A more general way to examine tabulated data is to use log-linear models described in Modern Methods of Analysis. 2.5 Multiple Response Data Surveys often contain questions where respondents can choose a number of relevant responses, e.g. 20  © SSC 2001 – Approaches to the Analysis of Survey Data If you are not using an improved fallow on any of your land, please tick from the list below, any reasons that apply to you:(i) Don’t have any land of my own (ii) Do not have any suitable crop for an improved fallow (iii) Can not afford to buy the seed or plants (iv) Do not have the time/labour There are three ways of computerising these data. The simplest is to provide as many columns as there are alternatives. This is called a multiple dichotomy†, because there is a yes/no (or 1/0) response in each case indicating that the respondent ticked/did not tick each item in the list. The second way is to find the maximum number of ticks from anyone and then have this number of columns, entering the codes for ticked responses, one per column. This is known as â€Å"multiple response† data. This is a useful method if the question asks respondents to put the alternatives in order of importance, because the first column can give the most important reason, and so on. A third method is to have a separate table for the data, with just 2 columns. The first identifies the person and the second gives their responses. There are as many rows of data as there are reasons. There is no entry for a  person who gives no reasons. Thus, in this third method the length of the columns is equal to the number of responses rather than the number of respondents. If there are follow-up questions about each reason, the third method above is the obvious way to organise the data, and readers may identify the general concept as being that of data at another level, i.e. the reason level. More information on organising this type of data is provided in the guide The Role of a Database Package for Research Projects. Essentially such data are analysed by building up counts of the numbers of mentions of each response. Apart from SPSS, few standard statistics packages have any special facilities for processing multiple response and multiple dichotomy data. Almost any package can be used with a little ingenuity, but working from first principles is a timeconsuming business. On our web site we describe how Excel may be used. 2.6 Profiles Usually the questions as put to respondents in a survey need to represent ‘atomic’ facets of an issue, expressed in concrete terms and simplified as much as possible, so that there is no ambiguity and so they will be consistently interpreted by respondents.  © SSC 2001 – Approaches to the Analysis of Survey Data 21 Basic cross-tabulations are based on reporting responses to such individual questions and are therefore narrowly issue-specific. A rather different approach is needed if the researchers’ ambitions include taking an overall view of individual, or small groups’, responses as to their livelihood, say. Cross-tabulations of individual questions are not a sensible approach to ‘people-centred’ or ‘holistic’ summary of results. Usually, even when tackling issues a great deal less complicated than livelihoods, the more important research outputs are ‘complex molecules’ which bring together  responses from numerous questions to produce higher-level conclusions described in more abstract terms. For example several questions may each enquire whether the respondent follows a particular recommendation, whereas the output may be concerned with overall ‘compliance’ – the abstract concept behind the questioning. A profile is a description synthesising responses to a range of questions, perhaps in terms of a set of abstract nouns like compliance. It may describe an individual, cluster of respondents or an entire population. One approach to discussing a larger concept is to produce numerous cross-tabulations reflecting actual questions and to synthesise their information content verbally. This tends to lose sight of the ‘profiling’ element: if particular groups of respondents tend to reply to a range of questions in a similar way, this overall grouping will often come out only weakly. If you try to follow the group of individuals who appear together in one corner cell of the first cross-tab, you can’t easily track whether they stay together in a cross-tab of other variables. Another type of approach may be more constructive: to derive synthetic variables – indicators – which bring together inputs from a range of questions, say into a measure of ‘compliance’, and to analyse those, by cross-tabulation or other methods. See section 2.8 below. If we have an analysis dataset with a row for each respondent and a column for each question, the derivation of a synthetic variable just corresponds to adding an extra column to the dataset. This is then used in analysis just like any other column. A profile for an individual will often comprise a set of values of a suite of indicators. 2.7 Looking for Respondent Groups Profiling is often concerned with acknowledging that respondents are not just a homogeneous mass, and distinguishing between different groups of respondents. Cluster analysis is a data-driven statistical technique that can draw out – and thence characterise – groups of respondents whose response profiles are similar to one another. The response profiles may serve to differentiate one group from another if they are somewhat distinct. This might be needed if the aim were, say, to define 22  © SSC 2001 – Approaches to the Analysis of Survey Data target groups for distinct safety net interventions. The analysis could help clarify the distinguishing features of the groups, their sizes, their distinctness or otherwise, and so on. Unfortunately there is no guarantee that groupings derived from data alone will make good sense in terms of profiling respondents. Cluster analysis does not characterise the groupings; you have to study each cluster to see what they have in common. Nor does it prove that they constitute suitable target groups for meaningful development interventions Cluster analysis is thus an exploratory technique, which may help to screen a large mass of data, and prompt more thoughtful analysis by raising questions such as:†¢ Is there any sign that the respondents do fall into clear-cut sub-groups? †¢ How many groups do there seem to be, and how important are their separations? †¢ If there are distinct groups, what sorts of responses do â€Å"typical† group members give? 2.8 Indicators Indicators are summary measures. Magazines provide many examples, e.g. an assessment of personal computers may give a score in numerical form like 7 out of 10 or a pictorial form of quality rating, e.g. Very good Good Moderate à  Poor Very Poor à ® This review of computers may give scores – indicators – for each of several characteristics, where the maximum score for each characteristic reflects its importance e.g. for one model:- build quality (7/10), screen quality (8/20), processor speed (18/30), hard disk capacity (17/20) and software provided (10/20). The maximum score over all characteristics in the summary indicator is in this case (10 + 20 + 30 + 20 + 20) = 100, so the total score for each computer is a percentage e.g. above (7 + 8 + 18 + 17 + 10) = 60%. The popularity of such summaries demonstrates that readers find them accessible, convenient and to a degree useful. This is either because there is little time to absorb detailed information, or because the indicators provide a baseline from which to weigh up the finer points. Many disciplines of course are awash with suggested indicators from simple averages to housing quality measures, social capital assessment tools, or quality-adjusted years of life. Of course new indicators should be developed only if others do nor exist or are unsatisfactory. Well-understood, well-validated indicators, relevant to the situation in hand are quicker and more cost-effective to use. Defining an economical set of meaningful indicators before data collection ought ideally to imply that at  © SSC 2001 – Approaches to the Analysis of Survey Data 23 analysis, their calculation follows a pre-defined path, and the values are readily interpreted and used. Is it legitimate to create new indicators after data collection and during analysis? This is to be expected in genuine ‘research’ where fieldwork approaches allow new ideas to come forward e.g. if new lines of questioning have been used, or if survey findings take the researchers into areas not  well covered by existing indicators. A study relatively early on in a research cycle, e.g. a baseline survey, can fall into this category. Usually this means the available time and data are not quite what one would desire in order to ensure well-understood, well-validated indicators emerge in final form from the analysis. Since the problem does arise, how does the analyst best face up to it? It is important not to create unnecessary confusion. An indicator should synthesise information and serve to represent a reasonable measure of some issue or concept. The concept should have an agreed name so that users can discuss it meaningfully e.g. ‘compliance’ or ‘vulnerability to flooding’. A specific meaning is attached to the name, so it is important to realise that the jargon thus created needs careful explanation to ‘outsiders’. Consultation or brainstorming leading to a consensus is often desirable when new indicators are created. Indicators created ‘on the fly’ by analysts as the work is rushed to a conclusion are prone to suffer from their hasty introduction, then to lead to misinterpretation, often over-interpretation, by enthusiast would-be users. It is all too easy for a little information about a small part of the issue to be taken as ‘the’ answer to ‘the problem’! As far as possible, creating indicators during analysis should follow the same lines as when the process is done a priori i.e. (i) deciding on the facets which need to be included to give a good feel for the concept, (ii) tying these to the questions or observations needed to measure these facets, (iii) ensuring balanced coverage, so that the right input comes from each facet, (iv) working out how to combine the information gathered into a synthesis which everyone agrees is sensible. These are all parts of ensuring face (or content) validity as in the next section. Usually this should be done in a simple enough way that the user community are all comfortable with the definitions of what is measured. There is some advantage in creating indicators when datasets are already available. You can look at how well the indicators serve to describe the relevant issues and groups, and select the most effective ones. Some analysts rely too much on data reduction techniques such as factor analysis or cluster analysis as a substitute for thinking hard about the issues. We argue that an intellectual process of indicator development should build on, or dispense with, more data-driven approaches. 24  © SSC 2001 – Approaches to the Analysis of Survey Data Principal component analysis is data-driven, but readily provides weighted averages. These should be seen as no more than a foundation for useful forms of indicator. 2.9 Validity The basic question behind the concept of validity is whether an indicator measures what we say or believe it does. This may be quite a basic question if the subject matter of the indicator is visible and readily understood, but the practicalities can be more complex in mundane, but sensitive, areas such as measurement of household income. Where we consider issues such as the value attached to indigenous knowledge the question can become very complex. Numerous variations on the validity theme are discussed extensively in social science research methodology literature. Validity takes us into issues of what different people understand words to mean, during the development of the indicator and its use. It is good practice to try a variety of approaches with a wide range of relevant people, and carefully compare the interpretations, behaviours and attitudes revealed, to make sure there are no major discrepancies of understanding. The processes of comparison and reflection, then the redevelopment of definitions, approaches and research instruments, may all be encompassed in what is sometimes called triangulation – using the results of different approaches to synthesise robust, clear, and easily interpreted results. Survey instrument or indicator validity is a discussion topic, not a statistical measure, but two themes with which statistical survey analysts regularly need to engage are the following. Content (or face) validity looks at the extent to which the questions in a survey, and the weights the results are given in a set of indicators, serve to cover in a balanced way the important facets of the notion the indicator is supposed to represent. Criterion validity can look at how the observed values of the indicator tie up with something readily  measurable that they should relate to. Its aim is to validate a new indicator by reference to something better established, e.g. to validate a prediction retrospectively against the actual outcome. If we measure an indicator of ‘intention to participate’ or ‘likelihood of participating’ beforehand, then for the same individuals later ascertain whether they did participate, we can check the accuracy of the stated intentions, and hence the degree of reliance that can in future be placed on the indicator. As a statistical exercise, criterion validation has to be done through sensible analyses of good-quality data. If the reason for developing the indicator is that there is no satisfactory way of establishing a criterion measure, criterion validity is not a sensible approach.  © SSC 2001 – Approaches to the Analysis of Survey Data 25 2.10 Summary In this guide we have outlined general features of survey analysis that have wide application to data collected from many sources and with a range of different objectives. Many readers of this guide should be able to use its suggestions unaided. We have pointed out ideas and methods which do not in any way depend on the analyst knowing modern or complicated statistical methods, or having access to specialised or expensive computing resources. The emphasis has been on the importance of preparing the appropriate tables to summarise the information. This is not to belittle the importance of graphical display, but that is at the presentation stage, and the tables provide the information for the graphs. Often key tables will be in the text, with larger, less important tables in Appendices. Often a pilot study will have indicated the most important tables to be produced initially. What then takes time is to decide on exactly the right tables. There are three main issues. The first is to decide on what is to be tabulated, and we have considered tables involving either individual questions or indicators. The second is the complexity of table that is  required – one-way, two-way or higher. The final issue is the numbers that will be presented. Often they will be percentages, but deciding on the most informative base, i.e. what is 100% is also important. 2.11 Next Steps We have mentioned the role of more sophisticated methods. Cluster analysis may be useful to indicate groups of respondents and principal components to identify datadriven indicators. Examples of both methods are in our Modern Methods of Analysis guide where we emphasise, as here, that their role is usually exploratory. When used, they should normally be at the start of the analysis, and are primarily to assist the researcher, rather than as presentations for the reader. Inferential methods are also described in the Modern Methods guide. For surveys, they cannot be as simple as in most courses on statistics, because the data are usually at multiple levels and with unequal numbers at each subdivision of the data. The most important methods are log-linear and logistic models and the newer multilevel modelling. These methods can support the analysts’ decisions on the complexity of tables to produce. Both the more complex methods and those in this guide are equally applicable to cross-sectional surveys, such as baseline studies, and longitudinal surveys. The latter are often needed for impact assessment. Details of the design and analysis of baseline surveys and those specifically for impact assessment must await another guide! 26  © SSC 2001 – Approaches to the Analysis of Survey Data  © SSC 2001 – Approaches to the Analysis of Survey Data 27 The Statistical Services Centre is attached to the Department of Applied Statistics at The University of Reading, UK, and undertakes training and consultancy work on a non-profit-making basis for clients outside the University. These statistical guides were originally written as part of a contract with DFID to give guidance to research and support staff working on DFID Natural Resources projects. The available titles are listed below. †¢ Statistical Guidelines for Natural Resources Projects †¢ On-Farm Trials – Some Biometric Guidelines †¢ Data Management Guidelines for Experimental Projects †¢ Guidelines for Planning Effective Surveys †¢ Project Data Archiving – Lessons from a Case Study †¢ Informative Presentation of Tables, Graphs and Statistics †¢ Concepts Underlying the Design of Experiments †¢ One Animal per Farm? †¢ Disciplined Use of Spreadsheets for Data Entry †¢ The Role of a Database Package for Research Projects †¢ Excel for Statistics: Tips and Warnings †¢ The Statistical Background to ANOVA †¢ Moving on from MSTAT (to Genstat) †¢ Some Basic Ideas of Sampling †¢ Modern Methods of Analysis †¢ Confidence Significance: Key Concepts of Inferential Statistics †¢ Modern Approaches to the Analysis of Experimental Data †¢ Approaches to the Analysis of Survey Data †¢ Mixed Models and Multilevel Data Structures in Agriculture The guides are available in both printed and computer-readable form. For copies or for further information about the SSC, please use the contact details given below. Statistical Services Centre, The University of Reading P.O. Box 240, Reading, RG6 6FN United Kingdom tel: SSC Administration +44 118 931 8025 fax: +44 118 975 3169 e-mail: [emailprotected] web: http://www.reading.ac.uk/ssc/