مدیریت عملیات در اقتصاد اطلاعات: محصولات، فرایندها و زنجیره های اطلاعات
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|7754||2007||16 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Operations Management, Volume 25, Issue 2, March 2007, Pages 438–453
The process of economic evolution from agriculture to manufacturing to services is nearing its end in the U.S. and other developed economies. Another major evolution along a different dimension is now underway: it is from a material-based economy to an information-based economy. In the past, the product–service dichotomy has proved useful as an organizing principle for the study of operations management. Today, however, a material–information categorization of products and services appears to be equally important and useful. The information sector now comprises the major share of the U.S. private economy and includes many of the largest industrial sectors and firms. We discuss the implications of this evolution for research and teaching in operations management (OM). The basic questions addressed here are: In what ways are information products, services, processes and chains similar to, or different from, those in the material world? To what extent is it possible to manage operations in information industries using the existing operations management concepts and techniques? The conclusions are mixed. To a great extent, traditional concepts are indeed applicable and useful. However, there are significant differences. For example, quantification and measurement pose a fundamental problem in the study of information industries. As a result, there are difficulties in analyzing some of the most basic OM issues related to productivity, cost, value, and transformation. Nevertheless, the process-centric methods of operations management can be quite effective in analyzing firms and industries that produce information goods and services. An understanding of process economics and information chains is also central to the analysis of competition given the impact of new technologies on processes, firms, information chains and information industries. We conclude that while there is much in the information sector that can be addressed with our current toolkit, some very interesting and challenging issues still remain open for research. From the perspective of management education too, operations management in the information economy is an area of growing importance, with some easy wins and some significant challenges.
As long as there has been organized commercial activity of any kind, there have always been “operations” to be managed. But the modern academic field of operations management (OM) can trace its roots to the scientific management and work-study techniques of Taylor (1911) and Gilbreth, 1911 and Gilbreth, 1912, the lot-sizing models of Harris (1913) and Camp (1922), and the shop floor models of Gantt (1916). In the service sector, the queuing analyses developed in telephony by Erlang (1909) and Palm (1957) have proved to be seminal in modeling many service contexts. Of course, the fundamental concept of a production function has been used in the field of Economics for many years, starting with agriculture and the production of simple goods. An early discussion of the special characteristics of the production function in service industries can be found in Fuchs (1968). Casual observation suggests that there has been a bias towards the manufacturing sector in teaching and research in OM in the past (Roth and Menor, 2003). But there is now an awareness of the large role of services in the economy, research on services is growing, and service operations management appears in most management curricula. Heineke and Davis (2007) and Chase and Apte (2007) describe this in their articles in this Special Issue. Today it could be fairly said that the shift to services for developed economies is far advanced without room left to go much further. It is time to address another significant shift in the economy—that towards the information sector. The motivation for this paper is that the information sector has already become the dominant part of the economy in the U.S., and this shift is ongoing and inexorable. Furthermore, it does not work to cast study of the information sector in terms of information technology, computer science or information systems, any more than manufacturing management could be cast in terms of mechanical engineering, reaction kinetics or parts machining. Like any industry sector, there are management questions related to operations, technology management, marketing, strategy, and human resources that need to be examined, although they may look a bit different, and may have to be sliced differently from the traditional functional divisions. Certainly, the traditional topics addressed in OM are very much in evidence in the information sector as well. We would include among these topics, the analysis of processes and process economics, the framing of decisions about stocks, flows and capacities, the management of productivity, quality, time, variety and cost, the design of products and services, the configuration of the systems and networks by which products and services are produced and delivered, the management of these production and distribution systems, the management and application of new technologies, and the analysis of resource and capability based competition. The size and growth of the information sector suggest that it behooves us to study the special features of this sector, and to develop new research and educational perspectives. 1.1. Information economy There are many definitions of data, information and knowledge. One operational definition of data is everything that can be sensed by humans (primarily heard and seen) and everything that can be converted into a symbolic (and therefore digital) representation. Information has been described as that subset of data, which is relevant, accurate, timely, and concise. It has the characteristic that it depends on the receiver as well as the sender. And, as a practical matter, information is usually generated by the processing of data by machines and/or humans. That we live today in an information economy is an assertion with which few people would disagree. We can define the information economy in many different ways and at several different levels of resolution. With respect to the latter, we could first look at the major sectors in the economy at the level of industries. A more detailed view might look at companies. A finer view would look at jobs. A still finer view would go to the level of operations or tasks. All these views provide somewhat different perspectives on the subject. In fact, it is useful to look at the information economy at different levels of resolution so as to serve different purposes. There exist two well-known early studies that have tried to define and measure the so-called information economy. In his pioneering work, Machlup (1962) studied what he called the “knowledge industry”. He identified the components of the knowledge industry and measured its contribution to gross national product (GNP). According to Machlup, 29% of the US GNP in 1958 was generated by the knowledge industry. Subsequently, using an approach that is quite distinct from the one used by Machlup, Porat (Porat and Rubin, 1977) measured the size and structure of the US information economy in 1967. Porat strictly followed the national income accounting framework. Machlup, on the other hand, had included a number of economic activities that were not part of the national income accounts. The approach followed by Porat is not perfect. Companies get lumped into sectors as though they do only one thing. Nevertheless, one of the major advantages of this approach is that the definitions are (reasonably) clear, data is available for many countries, and the results are reproducible and repeatable. Porat divides the information economy into two sectors: the “primary information sector” and the “secondary information sector”. The primary sector is defined as including all industries that produce goods and services that intrinsically convey information or are directly used in producing, processing or distributing information for an established market. Thus, the primary sector includes “information goods” such as computers, as well as services such as telecommunications. The secondary sector is defined to “include all information services produced for internal consumption by government and non-information firms”. It comprises most of the public bureaucracy and all of the private bureaucracy. The public bureaucracy comprises all the informational functions of the federal, state and local governments. The private bureaucracy is that portion of every non-information firm that engages in purely informational activities. It produces information services similar to those in the primary sector, such as data processing and library services, but which are not transacted in markets. See Porat and Rubin (1977) or Apte and Nath (2007) for detailed definitions of these sectors. Porat estimated the “information sector” to be 46% of the GNP in 1967. An OECD study (1981) using Porat's methodology, estimated the U.S. information sector to be 49% of the GNP in 1972. A study by Huber and Rubin (1986) that followed Machlup's methodology, estimated that the knowledge industry had only grown to about 34% in 1980, suggesting substantial differences in the Machlup and Porat approaches. Finally, following Porat's approach, Apte and Nath (2007) estimated that the information sector contributed 63% to the GNP in 1997. These numbers suggest that the information or knowledge economy, variously defined, has been a large part of the U.S. economy for many years—long before the advent of computers, the Internet, mobile phones and the dot.com boom-bust, and that the share of this sector in the economy has continued to grow steadily. 1.2. A framework for economic evolution The product–services dichotomy has proved to be a useful tool in categorizing operations problems. Most standard OM texts use it to highlight the differences in process characteristics and management requirements across different firms and sectors. In this issue of the Journal of Operations Management, Chase and Apte (2007) trace the history of research in Service Operations. In the preceding discussion, we have presented another useful dichotomy which could be described as material versus information, physical versus symbolic, or to use the popular phrase, atoms versus bits. We can overlay these two dichotomies to give us the obligatory 2 × 2 table (see Table 1). We have filled in the cells with examples; you may want to add a few of your own. First note that certain physical manufacturing and service examples (e.g., computers, telecom) fall in the information sector following the definition by Porat. In point of fact, many industries do not really lie entirely inside one cell. For example, both Machlup and Porat arrived at nearly identical results about the health care industry: it breaks down just about evenly across the material and information sectors. Fig. 1 uses data from Apte and Nath (2007) to estimate the value-added contributions to the 1997 GNP of the four divisions of Table 1, presented as percentages. Since several sectors including government are not included, the percentages are relative only to the totals across these cells. These numbers should not be taken as gospel, since there are many assumptions involved in making the estimates. However, their relative magnitudes are quite robust. These results underline the importance of the information and service sectors and especially that of the information services quadrant which is the confluence of the two major trends: it comprises more than 50% of the private economy. Furthermore, this sector is growing while the physical product sector is shrinking. We think that these numbers are persuasive. The information economy is now a reality, and the information sector and especially information services will dominate management concerns and management activity in the future. It also appears that in the near term, there are likely to be substantial impacts from information technology on the service sector that will demand considerable attention not only from managers and management researchers, but also from policy makers. If one looks for the causes underlying this pronounced and real shift, technology is certainly a driver. But an equally important reason is that other sectors of the economy have been highly efficient. Clark (1940) conjectured that the sectoral differences in productivity would lead to a situation whereby a majority of the labor force would no longer be engaged in agricultural or manufacturing, but in services. That conjecture seems to have come true. The consequences of low productivity in services were also described by Baumol, 1967 and Baumol, 1985. Today, agriculture represents only a small part the labor force and the GNP in the US, not because of a reduction of per capita or total consumption of food, but because the sector has been extremely productive. Similarly, the manufacturing sector is shrinking because of relentless productivity gains in manufacturing coupled with outsourcing, not because we are consuming less of physical products. Finally – and this is crucial to the rest of our discussion – the growth of the information economy is very much tied to developments in information logistics which have changed the economics of processes and value chains. In the next section, we look at what operations management in the information sector means. The intent is to raise issues, ask questions, and suggest some interesting directions for research. We start with a brief note of caution about a fundamental problem for management science in the information industries. Then we discuss the special characteristics of information processes and track the effect of information technologies on end-to-end information chains in different sectors, using the categorization in Table 1. Finally, we discuss how some traditional methods of analysis in OM translate to these sectors, and where there appear to be opportunities for new contributions.
نتیجه گیری انگلیسی
The premise of this paper is that the U.S. and, indeed, all developed countries are moving towards becoming true information economies. The emerging economies have farther to go but will also move much more rapidly towards a similar pattern. In the field of operations management we have long recognized the importance of services even if we have tended to dwell too long on traditional manufacturing. Now we need to recognize the implications of the shift from a material to an information economy. We earlier mentioned a research bias towards manufacturing. Similarly within services, there is a research bias towards physical services. The latter tend to involve large complex systems with a lot of moving parts, where our analytical OR techniques find ready applications. So, in fact, there is no shortage of work on topics like distribution, transportation, vehicular scheduling, time-tabling, nurse-scheduling, medical clinics and even theme parks. But there is much less seen on financial services, software production, professional services, business services, content management, publishing, etc. Here we have just scratched the surface of this topic. We have described some of the macro level issues that are visible; there is much more that could be said about the details of process economics and process analysis. We have made our own attempts at analyzing problems in the information economy: indeed the problems are novel and not easily handled by traditional tools and methods. But this is where the research opportunity lies. And we can at least start to conduct case studies and to collect process information that will enable us to take the next steps. There is a large and growing literature on many of the topics that we have mentioned. We cannot hope to review it here, but some examples include information product quality (Ballou et al., 1998), pricing of information goods (Bakos and Brynjolfsson, 1999 and Nault and Dexter, 1995), technology and information (D’Avolio et al., 2001) and the economics of information (Brynjolfsson et al., 1994 and Haltiwanger and Jarmin, 2000). In our own current research we are proceeding on several fronts including an edited volume containing research articles representing the state of the art in research on the emerging area of managing in the information economy (Apte and Karmarkar, 2007a), case studies (Bashyam and Karmarkar, 2000, Chaudhary et al., 2007 and Choi, 1996), industry studies (Andersen et al., 2006, Chang et al., 2007, Chaudhary et al., 2007 and Karmarkar, 2000), global surveys of practice (Karmarkar and Mangal, 2007), models of operations management (Apte et al., 2006 and Karmarkar, 2006b), knowledge management in operational processes (Mason and Apte, 2004), and analytical models of operations strategy (Carr and Karmarkar, 2006, Bashyam and Karmarkar, 2004, Choi et al., 2006 and Corbett et al., 2006). The scope and direction of the UCLA Business and Information Technology (BIT) Project under which some of this work was produced is described in Karmarkar (2006a). We end with a list of questions which we would like to be able to answer about operations in the information sector. We are working on some of these ourselves: • What is a good process model for describing information- and knowledge-based services? The “route sheet” or traditional process models are inadequate: is there a good alternative? • If quantities are not measurable, how do we address cost, quality, productivity, and value? Are there good proxies that can be empirically tested and validated? • Quality measurement and definition is a particularly complex issue, both for process (conformance) quality and output (performance) quality. A few specialized examples do exist (e.g., Bashyam and Karmarkar, 2000). But is there a general template that would work for quality in information products and services? • The cost model for information is highly specialized and varies by type of information. The issues to be analyzed include first copy/second copy economics, the characteristics of information obsolescence (news is short lived, theorems are not), the economics of creative production (from software to scripts), the economics of data, document and content management. Is a general cost model possible, or do we need several? • There are similar difficulties on the valuation side especially since there is likely to be great heterogeneity in value depending on the characteristics of the consumer. With products or standardized services, the solution lies in market valuation of the transacted good. But with interactive and responsive services (ranging from consulting to education) the problem is harder. Does not the value model have to include customer characteristics as well as product and service characteristics? • We have tools like data flow diagrams at the detailed level: these are too fine and too complex for management purposes. Can we develop a categorization for information operations that is useful from the operations management perspective? • What is the right model for “order release”? What methods can help us to manage information task management and requirements planning? How about a bill-of-materials for information assembly operations? • What are the cost and resource characteristics of information operations that will allow the development of planning and capacity management methods? • Storage costs for information are very low, but partly as a result, the costs of access and search are more of an issue. Add in obsolescence, and the costs of purging and renewal also start to matter since they are hard to automate. How are these factors to be modeled? • Suffice it to say that we could continue at length into areas of systems design, service design, strategy and competitive modeling. We look forward to hearing from our colleagues about their successful research on these and related topics. The future of operations management will not suffer from a dearth of interesting and important issues.