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The Knowledge Imperative Index (KIX) - A Measurement Model - Malaysia
Illustrations of the original text are excluded
Source: National Information Technology Council
This paper explores the development of Malaysia's Knowledge Imperative Index (KIX) within the following framework:
2. National Information Technology Agenda (NITA)
2.1 Need for a Knowledge Imperative Index (KIX) was first raised by the Malaysian Government as a means of monitoring and evaluating the National Information Technology Agenda (NITA). As one of the key national development strategies, NITA is aimed at transforming Malaysian society into an information or knowledge society by the first quarter of the next century. This 21st century civil society is envisaged as being fully developed socially, economically, politically and spiritually. Towards this end, NITA duly recognizes that Information and Communication Technology (ICT), in its contemporary form, is one of the key enablers of higher productivity, increased competitiveness and improved social cohesiveness. All these in turn are necessary conditions for improving the quality of life and building information and knowledge societies. This is possible because of the way ICT facilitates and enables the creation, distribution and utilization of data, information, knowledge and resources. However, this may not be the sufficient condition for building knowledge based civil society, if individuals and communities are not willing and prepared to embrace the emerging ICT opportunities in a proper manner.
2.2 The impact of modern ICT at all levels of society is accentuated after the commercial introduction of the Internet in 1982 in the United States. Prior to that the global society is connected in a limited way. Consequently, access to data and information was limited, too. The limitations are basically subjected to geography, societal and cultural factors. As a result of the Internet's on line and real time connectivity, the convergence of technology, people and content features, which is now expanding rapidly worldwide, these barriers are breaking down. The access to data and information is growing by leaps and bounds. Information is transported globally in various forms such as text, graphics, audio signals, video signals, in animation or still form and singly or in an integrated fashion. People able to communicate efficiently and effectively and able to share information and knowledge irrespective of color, race and creed. New platforms, environments, protocols and standards as well as new markets and opportunities are emerging worldwide in business sector. At the same time, this whole new phenomenon has led to the formation of virtual communities engrained with new culture of knowledge and resource sharing. These phenomena are also growing at an unprecedented rate and Malaysia is no exception ever since the commercial introduction of the Internet in 1992. The policy formulators and people at all levels of society have been concerned about the impacts and the effects of ICT and global interconnectedness. This has led to the inception of Knowledge Imperative Index (KIX) measurement in NITA.
3.1 KIX is a means of gauging the level of change in the formation of an information or knowledge society, arising from the impact of contemporary Information Communication Technology (ICT). The contemporary ICT is driven by microelectronic technology.
3.2 KIX has both qualitative and quantitative dimensions.
3.3 The qualitative aspect covers projects, programmes, regulations and annual conferences pertaining to ICT and knowledge society development. Annual reports, national development plans, research papers and conference materials record the qualitative dimension of progress in ICT.
3.4 The quantitative aspect covers statistical measures on ICT and knowledge society developments. This paper is concerned about this aspect.
B. Conceptual Framework: Knowledge Imperatives
4. The Knowledge Hierarchy Defined
4.1 Data1 are observable facts or assumptions, while information1 refers to processed data in a meaningful context for and by an individual. When one adds judgement to the processed information and internalizes it in a context, it becomes knowledge. By incorporating the ‘appropriate’ moral and spiritual values that are acceptable and beneficial to a particular society or culture, knowledge is regarded as wisdom.
4.2 This whole spectrum can be represented hierarchically to represent the continuity and links in the structure. Data, being voluminous and expressible in codes and bytes, occupies the broader base. Information, knowledge and wisdom, being derivatives of data, accordingly take positions nearer the apex. Their position in the hierarchy indicates their relative importance, with an inverse relationship of quantity to quality. Of the four components, wisdom has the highest status, but as both its meaning and measurement are controversial this paper will limit the discussion up to the level of knowledge.
4.3 These definitions and assumptions, and indeed the structural representation of data to wisdom, are particularly important in developing criteria for measuring data workers, information workers, knowledge workers, an Information Society and a Knowledge Society.
5. A Classification of Knowledge
5.1 The philosophy of knowledge is a complex subject, which is beyond the scope of this paper. Nevertheless, a basic understanding of the concept of knowledge is vital in developing appropriate measurement criteria for the various types of knowledge. Researchers and scholars have identified various types of knowledge. In the interests of clarity, only two web sites will be mentioned in this discussion. The web site at http://dpm.unige.ch/tecfa/publicat/peraya-papers/ocde/ocde11.html classifies knowledge into five categories. They are meta knowledge, involving general cultural and philosophical assumptions; milieu which is about the local environment; tacit knowledge which is rooted in practice and experience; contingent knowledge which relates to on the spot learning; informal knowledge which is about applying rules of thumb or tricks of the trade; formal knowledge, dealing with theories and formulae usually available in the form of text; and instrumentality, concerning knowledge embedded in tools and instruments. As can be seen, these classifications are not distinct. Their overlapping meanings pose difficulties in designing specific statistical criteria for measurement.
5.2 The web site at http://www.mcb.co.uk/courseware/mba/im-006.htm, describes the knowledge spectrum into two broad aspects: tacit knowledge and explicit or codified knowledge. By definition, tacit knowledge is described as personal and context-specific as it is uniquely embedded in a person and therefore hard to formalize and communicate. Tacit knowledge in a person also varies over time as it is, affected by experience, exposure, perception and life-long learning. In support of this, a document published by the Organization for Economic Co-operation and Development (OECD,1996) explicitly stated that tacit knowledge deals with know how and know- who, where the former refers to skills or the capability to do something, while the latter involves information about who knows what and who knows how to do what. On the other hand, explicit or codified knowledge refers to knowledge that is transmittable in formal, systematic language and which is presumed to be measurable. The same OECD document simply puts this type of knowledge as know-what and know-why, where know-what refers to knowledge about "facts" and know-why to scientific knowledge of the principles and laws of nature.
6. Assemblages of a Knoledge System
6.1 Measurability basically deals with statistical criteria. Before one can formulate the statistical criteria, the clarity on basic structure and characteristics of the subject matter under study is essential. As a matter of fact, understanding the key historical milestones that led to the development of today’s knowledge system is also equally important. In particular, it will facilitate identification of the scope and coverage of the measurement model especially when the knowledge system is known to have both modern and predated tools and techniques.
6.2 Like any other system, a knowledge system is also made up of many assemblages and imperatives. These include the contents per se, methods, processes, procedures, infrastructure, organizational network, institutions, modus operandi, inter linkages and evolutionary processes.
6.3 Most historians and technologists will agree that the tools and techniques of information technologies have been at the core of any human civilization. Notably, new inventions and innovations have been introducing greater efficacy and value in the development of a knowledge system. Nevertheless, technology on its own cannot produce or distribute knowledge without the involvement of people. Conversely, knowledge processes cannot take effect efficiently and effectively without technology. This has been the case since the beginning of human history when the spoken word was the earliest known form of information technology, perhaps between Adam and Eve. In this rudimentary communication technology system, the assemblages and imperatives are the spoken words as content; air as the technological link for the propagation of sound waves; and Adam and Eve as the people element.
6.4 As human history progressed, more sophisticated computing and communication media, information and content development emerged progressively. The earliest developments in this series, besides the spoken word, were writing on clay tablets, papyrus, tree leaves or animal skins; carving on wood or in caves; and the painting of pictures on walls. Along side this, number systems were also developed. In particular, the present system that was introduced by the Mesopotamian and Indus civilizations revolutionized information systems.
6.5 With the growing need for efficiency and effectiveness, the ancient computing sector registered the invention of the abacus, mechanical orchestra and Babbage’s analytical engine. Subsequently, the introduction of electrically driven data processing using punched cards and Hollerith’s automatic census tabulating machines paved the way for handling and disseminating voluminous data and information on a wider scale. However, these computing tools and techniques became obsolete with the advent of modern electronic computing technology in the 1940's. This was followed by microprocessor chip technology in the 1970’s, which completely replaced the older technologies. These modern technologies are noted not only for handling voluminous data but also for their inexpensive and speedy processing and dissemination of information across the globe. This phenomenon has contributed significantly to the information revolution we are experiencing today.
6.6 On the communication front, technology evolved from ancient Egyptian hieroglyphics, the Phonecian alphabet, jungle drums, smoke signals, carrier pigeons and men carrying messages across borders on foot, to printed material and photography on metal plates. However, communication was limited by geography until the invention of the Morse telegraph system in 1835. The Morse system enabled messages to be sent over a distance in the form of coded signals using electric pulses and marked the inception of on-line communication. Following this invention, other breakthroughs in modern communication emerged over the years. These include high-speed printing, transatlantic cables, telephony, radio, motion pictures, live telecasts, television and satellites.
6.7 Although the world has undergone great upheavals in technology and content, traces of old methods and modes of ICT are still found in more traditional or backward societies. Malaysia is no exception as there are still remote areas where the use of old tools is still popular. However, the KIX model cannot incorporate all evolutions and iterations of the past knowledge system. Some of the components and processes of earlier systems are not only becoming obsolete but are irrelevant and insignificant as far as present societal development processes are concerned. The KIX model identifies the advent of microelectronic technology as the single most distinctive factor responsible for replacing irrelevant technology and applications.
6.8 As a result of technological developments in the microelectronics sector, the convergence of computing, telecommunications, content and people is on the rise. Concomitantly, on-line connectivity and real time interactivity is expanding geographically and converging rapidly, giving rise to new interconnected communities worldwide. The world had never experienced these features before 1982 when the Internet was introduced commercially in the United States.
6.9 Online connectivity is defined as the electronic linking of one computer system with others for communication or the broadcasting of audio and/ or visual signals in still or animated form. Real time refers to a spontaneous or instantaneous way of acting on one another or with one another. Interactivity indicates the involvement of at least two people in an activity or system.
6.10 The activities and processes in a knowledge system also change with greater complexity, resulting in the emergence of new features and characteristics. Activities involving knowledge may take place in isolation or in combination. They can be simple or complex, depending on the need and nature of the activity. For instance, know-what and know-why type of information or codified knowledge can be obtained through reading books, attending lectures and accessing databases. With the introduction of the Internet, the availability of such information from networked computer systems worldwide is expanding rapidly. This new phenomenon has grown to such an extent that knowledge seekers now have to cope with new issues such as the explosion of information, authentication, privacy, validity, reliability and ethics. Know-how and know-who types of knowledge, on the other hand, arise from a variety of practical experiences. These include apprenticeships, the building of social relationships, business dealings, attendance at educational institutions, research, and dealing with a network of academic experts. (an extract from OECD 1996).
6.11 The level and commitment of people involved in the present knowledge system also varies greatly. These depend on their experience, expertise and needs. Despite technological sophistication and complexity, the knowledge system is also becoming increasingly versatile, flexible and user-friendly.
6.12 In the old days computer experts were directly engaged in creating and manipulating complex systems. The system’s stakeholders were consulted about system requirements, and the end users only appeared at the tail end of the process to endorse the usability of the whole system. Today, the scenario is fast changing with the appearance of more user-friendly hardware and applications. A person without a formal education in information technology is also able to develop simple systems and extract material that interests him. Even a novice is capable of retrieving material at an Internet café. An expert user, especially one in an office environment, may possess the skills to create and manipulate sophisticated systems to generate an array of information and disseminate it as useful codified knowledge. However, these two extreme examples have one thing in common: whatever the nature and requirements of the activities involving information or knowledge, in order for each process or person to function efficiently and effectively, the system must have the right form and the appropriate capacity and capability.
6.13 In a nutshell the foregoing indicates that the assemblages, correlates, modus operandi and ponens of the knowledge system have been continually changing and becoming more complex; in some instances, overlapping in form and meaning. Therefore, any attempt at measuring the knowledge system without detailing its structure, inter-relationships and components in a distinct manner will result in problems. Identifying the structure of the knowledge system is particularly vital for outlining the scope of study, identifying the appropriate variables, creating a data collation mechanism and making institutional arrangements. The model’s assumptions are also to be explicitly spelled out to facilitate the development of KIX’s measurement mechanism.
7. The Measurability of Knowledge
7.1 The first question one tends to ask is whether an abstract entity like knowledge can be measured. As the famous management guru Peter Drucker said, "missions" are always intangible, whether of business enterprises or of social service institutions. Intangibles are difficult to measure but Drucker cited operational objective from which clear and measurable goals with respect to product line, service, assortment, price and market penetration could be derived. He adds "saving souls" as the mission of a church is totally intangible. However, the goal of bringing at least two-thirds of young people of the congregation into the church and its activities is easily measured. Similarly, "health care" is intangible. But, the goals for a maternity ward such as the number of postpartum infections of mothers not exceed one half percent of all deliveries fairly easy to measure. In other words, if you cannot measure something in quantitative sense then focus on manifestations and reflections of abstract and intangible items. Though he said this in the context of management, the pertinent point he made also applies to knowledge, which presumably has both measurable and non-measurable aspects. From the foregoing classifications and definitions, one can deduce that certain aspects of the data to knowledge spectrum can be measured - and these are the main concern of this paper.
7.2 Tacit knowledge is difficult to codify and measure (Lundvall and Johnson, 1994, OECD 1996). This is only true to a certain extent. Socially embedded knowledge per se is impossible to quantify and measure. It is not like certain physical quantities that can be measured using gadgets or standardized procedures and methods. For example, heat can be measured using a thermometer, and the diameter of the earth can be determined using the law of gravitational forces between two masses. Similarly, in the case of tacit knowledge owners like doctors, IT technologists, bakers and farmers, the characteristics and traits that are outwardly manifested in them can be measured. These measurable attributes include their qualifications, profession, level of education, skills, level of exposure, and years of working experience. As a matter of fact, these outward traits are the underlying factors that tend to influence the level and quality of tacit knowledge.
7.3 The developed blocs like the USA, Japan and Europe have high literacy rates. The quality of education in these nations is notably high. They produce a large number of degree holders annually. The subjects that these graduates major in also cover a variety of fields. As a result these developed nations tend to have a high proportion of research and development scientists who invariably contribute a great deal to modern science and technology. Today, all modern disciplines have well established and defined systems of knowledge, methods and procedures. The developed nations are enriched by these disciplines, thereby achieving a higher ranking as far as knowledge is concerned. Their rankings are higher, not only in the dissemination of information and codified knowledge, but also with regards to tacit knowledge.
7.4 For qualitative tacit knowledge, it is necessary, but not sufficient, to have a high proportion of scientists in all disciplines. The eagerness of these scientists to explore their particular field is equally important. However, it is quite difficult to measure this unless a special set of questions is canvassed regularly. Soliciting information about the activities of scientists through primary approaches is an expensive affair, and may not stand up to a cost benefit analysis. In the absence of specific and direct data, readily available macro measurements in the present statistical systems like number of knowledge workers by profession, qualification, experience, field of study would be sufficient to give a proxy indication on growth pattern and characteristics of tacit knowledge developments in a society.
7.5 The codified aspects of data to knowledge are measurable. Traditionally, the source, types and quality of printed materials such as the number of libraries, newspaper readership, radio listening, television viewing et cetera are considered indicators for codified knowledge. Today the computers, with their high-speed capacity and capability able to provide the requisite computational facility to express the quantum of codified knowledge in terms of bytes or binaries. Besides that, the characteristics and traits of codified knowledge owners or producers also can be assessed through primary studies. The assessment even can be evaluated by social, economic and demographic characteristics. More importantly, statistical system needs to be instituted if regular supply of such information is collected especially for time series comparison.
7.6 The other dimensions that can be measured in the whole knowledge system are the imperatives in their tangible or intangible forms and manifestations. These include items like production, export and import values and numbers of hardware and software, PC penetration rate, IT literacy rate, quality of life index et cetera, to name a few.
8. Model Assumptions: Sociotechnology Model
8.1 KIX is perceived as a sociotechnology model. Traditionally information and knowledge contents are very much confined to individuals whose connections are constrained by geographical confines, time and rudimentary modus operandi. In such a societal setting and structure, the flow and sharing of information, knowledge and resources are restricted. People were compelled to travel to distant land to solicit even the codified knowledge, which are mostly stacked in libraries or in standalone personal computers and databases around the world. Such societies have no access to using modern computers and telematics. But, today people have become inextricably inter-wined with technology ever more than previously especially by adopting and adapting to Internet technology. Concomitantly, people are experiencing changes in working systems, societal living, institutional arrangements, life style and human relationships, giving rise to a number of paradigmatic changes as information age characteristics. These include digital era, information or knowledge explosion, knowledge driven economy, e-commerce, teleworking, rise of knowledge workers, changing governance, cyber communities, virtual networks et cetera. These changes are, in turn, attributes directly or indirectly as imperatives for the functionality of various aspects in the knowledge systems and thus bringing further enhancements in technology and social dimension, which inherently has linkages with economy, politics and environment.
8.2. A number of other assumptions are also made in developing the model. They are as follows:9.1 After examining the evolution and the structure of the contemporary ICT sector as well as the underlying assumptions, the KIX Model apportions the whole range of imperatives of knowledge systems into hard and soft elements. The hard elements deal with technology dimensions in terms of technology components and key evolution processes. The soft issue pertains to people dimension including institutions. The structure, scope and coverage as well as key features of technology and people dimension considered in developing KIX are mentioned in subsequent paragraphs. This is particularly important for identification and appropriation of variables and to facilitate information canvassing and processing processes when surveys are launched.
10.1. Technology dimension key features are as follows:10.2 Traditionally, the computing and telecommunication in terms of research and development remained independent of one another until the advent of modem technology. The modem, which provides modulation and demodulation capability enables the conversion of analog signals to digital and vice versa. As a result of great technological feat and upheavals, today’s information system has the following characteristics:
10.3 The traditional IT definition quoted in standard text books by academic and curriculum requirements include older technology such as document filing systems, mechanical accounting machines, printing and cave drawings, besides the modern ones. The model precludes the coverage of older ICT technology, as they are becoming obsolete, insignificant and irrelevant to modern information or knowledge imperatives.
10.4 The knowledge imperatives in the modern system also can be broadly classified into electronics and non-electronics components. The electronically driven technologies are central in the development of the knowledge system in the present digital era. However, the non-electronic components such as books, libraries, pen, pencils et cetera attributes to knowledge enhancement and can be considered as an imperative under people dimension.
10.5. The model by its assumption and definition identifies key technology features and manifestations as follows:11.1. The people dimension has the following components:-
11.2 Key features of information access:
Diffusion is defined as the process by which an innovation is adopted and gained acceptance by members of a certain community. A number of factors interact to influence the diffusion of innovation. The four major factors that influence the diffusion process are the innovation itself, how information about the innovation is communicated, time and the nature of the social system into which the innovation is being introduced (Roger, 1995 & http://fso.arizona.edu/dickportfol…ssertation/theories/diffusion.html). In KIX context the primary impact of ICT technology on people is construed as technology diffusion or information access. No one can impose technology on people unless there is a willingness to adopt and adapt to changes on the part of an individual, perhaps even organizations and establishments.
11.3 The primary impact is manifested or reflected in the supply, spread and accumulation of information and communication technology products and services.11.4 The measurable aspect of the primary impact is the technology product and services that facilitate information access processes are radio, television, computers, video, multimedia products et cetera.
11.5 The indicators best describe the technology diffusion process are number of personal computers shipped, PC penetration rate in agriculture sector, number of wireless phone et cetera. In this context an information society is simply defined as the one constitute individual who has access to information such as listening to radio, watching television, using telephony services, surfing Internet for leisure and entertainment et cetera.
11.6 Knowledge Acculturation Features
The information access or diffusion does not relate or reveal the intensity of information retrieval and usage in an individual life at work place or home. For example, a school may receive 20 computers, which can provide ample opportunity for information access, perhaps via Internet. This does not mean that the teachers and pupils are computer literate or IT competent or knowledge workers unless they learn to use the tool to a maximum benefit. Even among the users, the level of ICT usage can differ, perhaps giving rise to various levels and types of knowledge workers. On this basis, the model defines acculturation process as a next step after information access or diffusion has taken place. As per definition, acculturation is the process of becoming adapted to a new or different culture with more advanced patterns.
Connotatively, in KIX context the knowledge acculturation process has two dimensions in its manifestations. The first part is the traditional players in a society, who creates, acquires, distributes and utilizes knowledge in enhancing social and economic values. This part comprises of teachers in the basic education system, lecturers and professors in the higher learning institutions, scientists in the research institutes and working professionals. The other part is the recent phenomenon where individuals use contemporary technologies in the creation, acquisition, distribution and utilization of knowledge. However, in both cases some level of education and expertise is prerequisite. Thus, the crucial factor in the whole knowledge acculturation process is the capability building. The type and the level of capability is determinable by assessing the intellectual content and duration, level, sophistication and competency in the usage of hardware and software technology. This simply differentiates, for example, a doctor without IT knowledge against the one who has and ready for new medical concepts like telemedicine. Similarly, a doctor young in IT knowledge compared against another doctor with well versant and competent in IT usage in medicine differ.11.7 Therefore, in a nutshell the measurable aspect of knowledge acculturation can be construed to human resource and intellectual built-up by level, type and category in a society.
11.8 The indicators include number of primary school teachers, number of engineering lecturers, number of applied science graduates et cetera.
11.9 Key features of knowledge effect:
The knowledge effect by its implicit meaning is the outcome or consequence of knowledge. In KIX context, it is the ‘deepening’ impact of ICT on individuals, societies and establishments.. In Malaysian context enhancements in multiculturality is also considered as an outcome of knowledge effect. However, this concept is only a conjecture and not proven with any hard data. The model also assumes improvement in quality of life or multiculturality itself is, in turn becomes, soft imperatives in the knowledge systems. This simply mean that when quality of a person or society improves, the level of preparedness for embracing and adopting new changes in work and play due to technological impact is also tend to rise. The converse also can be true.
11.10 The KIX model acknowledges information and knowledge is the inherent factor in social, economic and spiritual development. Therefore, development is regarded as the manifestations or reflections to indicate quality of life.
11.11 Thus, the manifestations of quality of life in various domains of life can provide the requisite measures for the knowledge effect domain of study. As such, the measurable pertain to development profile covering social, economy, demography, health, communication, environment and politics.11. 12 Some of the leading indicators for the quality of life measure include infant mortality rate, number of doctors per 1000, GNP per capita et cetera.
11.13 Key features of knowledge enabling domain:
Besides hard technology, individuals and societies, a number of institutional framework and arrangements also must be in place in the development of a knowledge system. Therefore, the institutional parameters are considered as imperatives under the knowledge enabling processes and activities. The KIX model classifies the knowledge enabling domain under people element or soft factors.
11.14 The knowledge enabling factors are basically manifestations of capacity building activities that attribute to the development of a knowledge system.11.15 For measurable purposes, the capacity building aspects can be broadly categorized into teaching institutions, training institutions, research and development institutions, licensing and permit issuance, regulatory framework, consulting agencies, programmes and projects et cetera.
11.16 Thus, the measurable indicators for this domain of study, to name a few, includes number of primary schools, number of Internet Service Providers, number of telecommunication permits issued, number of patents, number of technology flows, number of projects in Multimedia Super Corridor and Demonstrator Application Program expenditure et cetera.
12.1 A variable in the KIX model is defined as an event or incidence that attributes or contributes directly or indirectly to the knowledge system, which constitutes technology, people and institution.
12.2 The foregoing paragraphs have depicted a number of examples of KIX variables by major or sub domain.12.3 The socioeconomic and demographic variables of people are very vital in monitoring and evaluating the development towards the formation of knowledge society. Such differential analysis can provide the indication on the equity distribution in information access or knowledge acculturation as well as knowledge effect. The standard socioeconomic and demographic characteristics of interest are by age, sex, race, marital, employment and occupation and industry status. Besides that, area analysis by urban rural classification or sub national levels such as state or administrative districts are also important indicators for equity distribution. These differential factors are important imperatives for providing a complete picture on the development of any knowledge system. However, such variables on ICT and knowledge society developments can only be generated through primary surveys, which is very much lacking at the moment.
13.1 The foregoing description briefly outlines the conceptual framework of the KIX measurement by elucidating the components, classifications and key features. The framework and structure are essential in apportioning or placing a variable into the appropriate domain and sub domain. A number of examples also have been cited in the above deliberations. However, in practice it is impossible to identify and incorporate all variables deem to attribute meaning to KIX model. A reasonable number of variables would suffice to give a full meaning to KIX measurement. The important consideration and criteria warrants attention in selecting the variables is its conceptual significance, data availability, validity, consistency and sufficiency as well as stability over time.
14.1 The ICT sector has a very limited and scanty data. Whatever data available are mostly from secondary sources, mainly compiled from records and documents of public agencies. Some of the data sought after are subsumed in the industry, occupation and product and trade classification systems. Most of these public agencies collate data for their internal use to facilitate policy formulation, program implementation as well for monitoring and evaluation activities. In the process, some of these statistics also appear in regular publications for public consumption. At the same time there is also a vast array of data are kept in strict confidence at data generating agency level or disseminated upon request but for restricted use only. However, the ICT data that are available in the current statistical system are generally not comprehensive enough to portray exact developments taking place in the information age. The reason for this is that the present statistical systems, not only in developing countries but also in most developed nations have not undergone a review or revamp in adjusting to an emerging information age phenomenon.
14.2 Being an emerging area of study, it is also impractical at this juncture to deliberate the full fledge meaning of the KIX representation. A model with full meaning can only be realized progressively as and when the requisite data permits. This requires realignment of present statistical system, in particular the industry, product, trade and occupation classifications, which have become obsolete for the new age technology. New surveys such as Internet Subscriber Study and Internet User Study are being initiated. This paper is an attempt to develop a prototype index using whatever data available from secondary sources.
15. Data Treatment and Assumptions
15.1 The prototype model the following assumptions were made in relation to data treatment, as follows:16.1 The traditional method of computing index, that is, dividing the present value with a fix base is found to be unsuitable for variable values with varying degree in magnitude and nature. In particular, the KIX model is made up of attributes differing in characteristics, domain meaning, scale and unit of measurement. The traditional index, shows erratic movement in the index values and can be very sensitive to magnitude of base value. Such indexes are also difficult to aggregate meaningfully as rate of variation greatly differs among variables.
16.2 Alternatively, the KIX model examines the use of logarithm concept to convert the variables into an index form. Inherently, log has the property of standardizing a variable value to a common base (say to base of 10 under common logarithm), and can be expressed in index power. The index power is interpreted as "level of a variable" at a point of time.
16.3 In the example the value 120 is reduced to a level of 2.0792, while 144 is reduced to a level of 2.1584 by logarithmic process. Though the number changed from 120 to 144, but the level changed from 2.0792 to 2.1584 over the period T1 to T2. This means the actual rate of change is 20 per cent, which is equivalent in meaning by taking the difference between 2.1584 and 2.0792, that is a logarithmic difference of 0.079. When the consecutive actual values increase by 20%, the corresponding change in logarithmic difference is a constant. In other words, when the actual values increase or decrease by a differing rate from one period (Ti) to another (Tj) the corresponding change will be reflected accordingly in the logarithmic difference. See the example below where a time series data is shown to illustrate these properties. The rate of change and logarithmic difference is constant between T1 to T4; when the rate of change increased, the logarithmic difference value also increased proportionately between T4 to T5.
16.4 The above example is cited to illustrate a property of logarithm. The rate of change can be useful to illustrate the up and down movement of a variable value as usually illustrated in a semi-log graph. Concomitantly, the rate of change measure in its percentage form cannot be converted into a meaningful index, as an index series needs to be expressed in a time series by comparing to a fix base value. On contrary, the KIX model chooses to view the meaning of logarithm in different context.
16.5 The KIX model attempts to monitor the CHANGE IN THE LEVEL OF THE VARIABLE, over time; that is by comparing the exponent power of a variable at time Ti to a fix base value given at time T1. The change in power or level change is expressed as an index number by multiplying by 100.
16.6 It can be seen from the examples above that the stability of the index movement is more pronounced in monitoring the level of change than the actual value change or rate of change; the measure of consecutive changes provide the indication. A careful examination of the result in the above example also indicates the level of change by 3.8 reflects a constant rate of change by 20 per cent in actual value and similarly, 4.7 reflects 25 per cent.
16.7 The merit of the Variable-Scaling Technique (VST), as KIX Model proposes is that a variable of any magnitude can be level to a comparable magnitude. For example, let say a variable values change from 1000 to 10,000. In common log term the values translate into 2 and 3 respectively. In other words, log property minimizes the variation present in the original data value by leveling process. The standardization technique provides a good criterion for combining or integrating variables of differing nature.
16.8 This technique holds for all non-zero variable value, as log of zero is not defined. However, the model does not rule out the possibility of non-zero values. For example, production of monochrome television is declining and it will assume zero value in the near future. In such cases, the model has the flexibility and versatility to drop such variables without affecting the value of index series especially when the average is based on large number of variables.
16.9 The model also assumes the base value of a selected variable is not equal to one in magnitude. The log value of one is zero, in which it cannot assume a base value under the proposed VST. However, in practice most variables assume value greater than. If there is any, then appropriate care has to be taken in data treatment. Since the computation are done using spread sheet, such discrepancies present in the data can be easily detected.
16.10 The KIX Model repeats the same computation process for all the Vk,d , where k denotes the variable and d indicates the sub-domain level. Accordingly, at sub-domain level an average value the index can be computed using simple average or geometric average. The geometric average provides greater stability, flexibility and versatility than the simple average especially when the model demands inclusion of new variables or exclusion of obsolete variables. This is particularly, an important criterion in KIX Model as it involves a number of technology variables, which in practice undergoing continual changes in its shape and form.
16.11 In a nutshell the KIX Model uses the following formulae:
Each Variable Index value is calculated as:
Iz = { Log ( Vn) / Log (V0) } * 100,
where Vn is the current value, V0 is the base value and log refers to logarithm; logarithmic quotient values of a variable at two points of time denoted as . Log ( Vt1 ) / Log ( Vt2 ), as divisor has property of scaling.
The Sub Domain Index value can computed using additive or geometrically as
Id = S ( Iz / k) * 100 , OR Id = P ( Iz)1/k * 100
where d is the domain name, Iz is the logarithmic index and k is the number of variables . Similarly, an integrated index measure at an overall level can be computed using similar formulae.
17.1 As per the definition of the model, a prototype result was generated as shown in Table below. The result is based on a total of 158 variables. The breakdown is also shown in the Table. The selection of variable for the prototype demonstration is based on the availability of secondary data.17.2 The sub domains of the technology component are not shown in the able due to lack of sufficient number of variables for each sub-domain. Within each sub domain, all variables are given equal weight. All sub domains within a major domain assigned equal weight. Ideally, speaking the effect of weight is negligible because of large number of variables In the computation process the year 1990 assumed as a base year, which is chosen arbitrarily.
17.3 The result shown in the Table is dubious, as the computation is based on limited and arbitrary data. However, for an illustration purposes attempt is made to interpret the findings. The overall KIX moved upward from 100 in 1990 to 114.2 in the year 1995. This means the level of knowledge imperatives rose by 14.2 percent over the five-year period; indicating both technology and people experienced progress in the present digital era. This can be seen further at sub domain level where the technology index registered upward movement by 14.0 percent. Similarly, the four components of people dimension recorded rise in the index value. Among them, the knowledge acculturation domain registered the highest movement, that is 21.5 per cent over the five year span. The figures shown in the Table also can be used for comparisons between the domains or as a time series data. For instance, the knowledge enabling sector showed an upward movement by 16.2 percent in comparison to only 8.5 percent for knowledge effect segment. Similarly, the overall index changed 5.3 percent in level from base year to 1991, while it registered only 3.5 percent change in level between 1994 to 1995
18. Merits and Demerits of KIX Model
18.1 The KIX Model in its formulation has a number of merits as follows:
16.1 The KIX Model is unique in concept and methodology and first of its kind in the world. The prototype model is developed to initiate a thinking process to develop a monitoring and evaluation mechanism for ICT era. A lot more effort is needed towards the full realization of the model. In particular, refinements are needed in defining the meaning of KIX, development of measurable concepts and definitions, improving methodology issues and institutionalizing data collation mechanism. For this, the existing statistical system needs a review so that the present primary surveys and secondary sources are tailored to provide the requisite data. This progression may take a couple of years as it involves a number of institutions and ranks in the bureaucracy. However, from the foregoing it can be seen that KIX can be a policy imperative measure in the digital era, once full model materializes.
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