The partial adjustment valuation approach with dynamic and variable speeds of adjustment to evaluating and measuring the business value of information technology

In this paper we develop the partial adjustment valuation approach in which the speeds of (partial) adjustment are assumed to be dynamic and variable, rather than fixed or constant, to assessing the value of information technology (IT). The speeds of adjustment are a function of a set of macroeconomic and/or microeconomic variables, observed and unobserved and, hence, become time-varying or dynamic and variable over time. The approach is illustrated by a practical application. The results imply that the constant speeds of adjustment may overestimate or underestimate the actual speeds of adjustment and, accordingly, may miscalculate the values of performance metrics. Thus, the partial adjustment valuation approach with dynamic and variable speeds of adjustment is more realistic and, more importantly, captures the changing patterns and trends of the adjustment speeds and the performance measures as well. As such, the partial adjustment valuation approach with constant speeds of adjustment fails to adequately explain the dynamic production process of a decision making unit. The empirical evidence also conflicts with the lopsided view that the productivity paradox does not exist in developed countries.     

In search of information technology productivity: Assessment issues

Despite the massive investments in Information Technology (IT) in the developed economies, the IT impact on productivity and business performance continues to be questioned. The paper critically reviews this ‘IT productivity paradox’ debate. It suggests that important elements in the uncertainty about the IT payoff relate to deficiencies in measurement at the macroeconomic level, but also to weaknesses in organisational evaluation practice. The paper reports evidence from a 1996 UK survey pointing to such weaknesses. Focusing at the more meaningful organisational level, an integrated systems lifecycle approach is put forward as a long term way of strengthening evaluation practice. This incorporates a cultural change in evaluation from ‘control through numbers’ to a focus on quality improvement. The approach is compared against 1995–96 research findings in a multinational insurance company, where senior managers in a newly created business division consciously sought related improvements in evaluation practice, and IT productivity.     

Productivity breakdown of the information and computing technology industries across countries

In this paper, we measure productivity growth of the information and computing technology (ICT) industries in 14 Organization for Economic Cooperation and Development countries over the 13-year period of 1978–1990. The ICT industries are the providers of essential information technology (IT) capital goods. This macro-level analysis seeks to find out how productively such IT capital goods are provided. The basic unit of analysis employed is the Malmquist Total Factor Productivity (TFP) index. The Malmquist TFP index is then decomposed into three constituent elements accounting for different sources of productivity growth: technological progress, efficiency change, and change in economies of scale. The approach of measurement is based on the concept of distance functions and employs the non-parametric frontier method of data envelopment analysis. Our results indicate that each country's ICT industry manifests its own particular patterns in various performance measures. Among the 14 countries examined, 10 had witnessed productivity growth in their ICT industries. Overall, these ICT industries are found more productive than other industries when compared with previous research. Further analyses reveal that (1) most of the productivity growth measured is due to technological progress; (2) efficiency change exerts a relatively small positive effect on productivity growth; and (3) the change in scale economies unfavourably affects productivity for most countries. Finally, practical implications for formulating IT policy are drawn from our results, and topics are identified for future research.     

Discovering the dynamics of smart business networks

This paper describes a simple diffusion process whereby to discover the dynamics of emergent smart business network structures and their performance in view of business collaboration patterns over time. They include the destabilizing effects of business relationship tie-up’s or break-downs, and are discussed various partner evaluation, filtering and self-preference strategies. Three real life cases of business network dynamics are discussed based on data from the high tech sector. Lessons learnt from such cases are reported regarding overall smart network dynamic parameters with respect to local interaction strategies.     

MEASURING PRODUCTIVITY AND ITS COMPONENTS FOR FISHERIES: THE CASE OF THE ALASKAN POLLOCK FISHERY, 1994–2003

Abstract Traditional productivity measures have been much less prevalent in fisheries economics than other measures of economic and biological performance. It has been increasingly recognized, however, that modeling and measuring fisheries' production relationships is central to understanding and ultimately correcting the repercussions of externalities and poorly designed regulations. We use a transformation function production model to estimate productivity and its components for catcher–processors in the Bering Sea and Aleutian Islands pollock fishery, before and after the introduction of a cooperative system that grants exclusive harvesting privileges and allows quota exchange. We also recognize the roles of externalities from pollock harvesting by incorporating data on climate, bycatch, and fish biomass. We find that productivity has been increasing over time, that many productive contributions and interactions of climate, bycatch, and fishing strategies are statistically significant, and that regulatory changes have had both direct and indirect impacts on catch patterns and productivity.     

IT外包知识共享行为的演化博弈分析

针对IT外包知识共享障碍的问题,在已有IT外包知识共享研究的基础上,依据演化博弈论建立了IT外包知识共享行为的演化博弈模型,通过求解复制动态方程与演化稳定策略,分析了影响IT外包知识共享行为的因素,并利用Matlab 7.6软件进行仿真。研究结果表明,知识可共享量、知识互补程度、信任、知识吸收转化能力、知识共享成本和风险以及激励机制等是影响IT外包知识共享行为的关键因素。最后提出相应的对策与建议。     

Fuzzy interaction regression for short term load forecasting

Electric load forecasting is a fundamental business process and well-established analytical problem in the utility industry. Due to various characteristics of electricity demand series and the business needs, electric load forecasting is a classical textbook example and popular application field in the forecasting community. During the past 30 plus years, many statistical and artificial intelligence techniques have been applied to short term load forecasting (STLF) with varying degrees of success. Although fuzzy regression has been tried for STLF for about a decade, most research work is still focused at the theoretical level, leaving little value for practical applications. A primary reason is that inadequate attention has been paid to the improvement of the underlying linear model. This application-oriented paper proposes a fuzzy interaction regression approach to STLF. Through comparisons to three models (two fuzzy regression models and one multiple linear regression model) without interaction effects, the proposed approach shows superior performance over its counterparts. This paper also offers critical comments to a notable but questionable paper in this field. Finally, tips for practicing forecasting using fuzzy regression are discussed.     

Productive efficiency and energy use: An historical perspective

The paper discusses long-term trends in relationships between energy use and the overall productive efficiency of the American economy. While total energy consumption grew strongly during the twentieth century, the intensity of energy use (i.e. the energy/GNP ratio) fell persistently much of the time. Thus, there were simultaneous long-term improvements in labor productivity, total factor productivity,and energy productivity. The historical record appears to be at odds with conventional beliefs that gains in productive efficiency depend upon the rising intensity of energy use in production processes. A key role in bringing about these counter-intuitive results is assigned to what is referred to as the energy-technology-productivity nexus, in which the quality of particular energy forms such as electricity and liquid fuels (along with closely linked changes in energy-using technologies) played a critical part in leveraging the overall efficiency of production. As a result of these energy form-dependent improvements in productive efficiency, outputs grew more rapidly than all inputs, including the inputs of energy. The more recent past stands in sharp contrast to the long-term record. While energy efficiency (as measured by energy/GNP) showed strong gains during the late 1970's and early 1980's, the growth in overall productive efficiency was severely retarded. Implications for the future of suggested linkages between the quality of particular energy forms and technological progress are considered.     

判断并解决线性规划“多反而少”悖论的逆最优值解法

现有研究通过调整线性规划模型的右端项来消除“多反而少”悖论,而该文提出并验证了悖论是由技术系数矩阵、目标函数系数以及右端项三者的不合理搭配造成的。首先,通过建立原-对偶模型来判断悖论现象存在与否;然后,将悖论问题转换成逆最优值问题进行解决,构建了通过调整目标函数系数以及技术系数矩阵来消除悖论的模型;最后,提出了判断并解决悖论的逆最优值解法,阐述了其优势与经济意义,并通过数值算例验证其有效性。     

Information technology and systems justification: A review for research and applications

Information technology (IT) such as Electronic Data Interchange (EDI), Radio Frequency Identification Technology (RFID), wireless, the Internet and World Wide Web (WWW), and Information Systems (IS) such as Electronic Commerce (E-Commerce) systems and Enterprise Resource Planning (ERP) systems have had tremendous impact in education, healthcare, manufacturing, transportation, retailing, pure services, and even war. Many organizations turned to IT/IS to help them achieve their goals; however, many failed to achieve the full potential of IT/IS. These failures can be attributed at least in part to a weak link in the planning process. That weak link is the IT/IS justification process. The decision-making process has only grown more difficult in recent years with the increased complexity of business brought about by the rapid growth of supply chain management, the virtual enterprise and E-business. These are but three of the many changes in the business environment over the past 10–12 years. The complexities of this dynamic new business environment should be taken into account in IT/IS justification. We conducted a review of the current literature on IT/IS justification. The purpose of the literature review was to assemble meaningful information for the development of a framework for IT/IS evaluation that better reflects the new business environment. A suitable classification scheme has been proposed for organizing the literature reviewed. Directions for future research are indicated.     

Machine learning applications in nonlife insurance

The literature on analytical applications in insurance tends to be either very general or rather technical, which may hold back the adoption of new important tools by industrial practitioners. Our goal is to stress that machine learning (ML) algorithms will play a significant role in the insurance industry in the near future and thus to encourage practitioners to learn and apply these techniques. After discussing the increasing relevance of data for nonlife insurance and briefly reviewing the major impact of digital technology on this business, we restrict our discussion to technical analytical applications and indicate where ML algorithms can add most value. We present two real examples: first a comparison of retention models for household insurance and then a dynamic pricing problem for online motor insurance. Both applications illustrate the advantages but also some of the difficulties of applying ML tools in practice. Finally, we mention some challenges posed by the use of ML in the industry and formulate a few recommendations for successful applications in insurance. This article is neither a tutorial nor an exhaustive review of technical ML applications in nonlife insurance. However, references for additional learning materials are provided.     

The impact of accessibility on the value of information and the productivity paradox

The value of information systems availability is analyzed in this study through theoretical models of information economics. The article employs the information structure model to assess the values of information systems under various situations, with particular examples of the impact of data accessibility level on the quality of decision-making.The study centers on the relationship between the information system's time and content characteristics and the value of the information. It suggests a method to model the utility considerations that lead to the choice of an information system. The entailed models are employed to illuminate certain facets of the productivity paradox.The results of the analysis indicate that there is a direct relationship between systems accessibility and its informativeness. Consequently, there are some aspects of the “Productivity Paradox” that may be explained by using these results. The article proves a number of theorems and discusses the theoretical and practical interpretation of the results.     

Linking routines to the evolution of IT capability on agent-based modeling and simulation: a dynamic perspective

IT capability as an important source of competitive advantage has been strongly emphasized in the strategic management literature, yet the formation and evolution of IT capability in the ever-changing business environment are not well explained. To fill this gap, this paper takes routine as the unit of analysis, depicts a micro-interpretation of the formation and evolution of IT capabilities from the routine-based and dynamic perspective, and uses the agent-based simulation methodology to simulate the evolutionary process of IT capability as well as to identify the underlying principles. In order to provide a better presentation of the evolutionary process, a routine-based view of the enterprise explicitly recognizes relationships of IT resources and capabilities. The simulation results show that the evolution of IT capability is a dynamic adaption and learning process. From the routine-based view, the evolution of IT capability is indeed the process of variation, selection, and retention for IT routines.     

The deterministic multi-item dynamic lot size problem with joint business volume discount

This paper considers the multi-item dynamic lot size model where joint business volume discount is applied for all items purchased whenever the total dollar value of an order reaches a certain level. Multi-item discounts are prevalent in practical applications, yet the literature has only considered limited instances of single-item models. We establish the mathematical formulation and design an effective dynamic programming based heuristic. Computational results disclose our approach obtains high quality solutions that dominate the best known heuristic for the simplified one-item case, and that proves vastly superior to the state-of-the-art CPLEX MIP code for the multi-item case (for which no alternative heuristics have been devised). We obtained significantly better solutions than CPLEX for the more complex problems, while running from 4800 to over 100,000 times faster. Enhanced variants of our method improve these outcomes further. This revised version was published online in June 2006 with corrections to the Cover Date.     

Transforming business using digital innovations: the application of AI,blockchain, cloud and data analytics

This study explores digital business transformation through the lens of four emerging technology fields: artificial intelligence, blockchain, cloud and data analytics (i.e., ABCD). Specifically, the study investigates the operations and value propositions of these distinct but increasingly converging technologies. Due to the dynamic nature of innovation, the potential of this ABCD hybridization, integration, recombination and convergence has yet to be considered. Using a multidisciplinary approach, the findings of the study show wide-reaching and diverse applications among a variety of vertical sectors, presenting exploratory research avenues for future investigation. The study also highlights the practical implications of these new technologies.

     

Improving the adaptability in automated vessel scheduling in container ports using intelligent software agents

Faster turnaround time of vessels and high berth productivity are paramount factors in container terminals for assuring competitive advantage in the shipping industry. An autonomous decision-making capability in the terminal is vital in achieving the required productivity. Vessel scheduling/berthing system in a container terminal is regarded as a very complex dynamic application in today’s business world. The Artificial Intelligence (AI) community has been researching in the field of intelligent (or rational) agents for more than a decade and implementations are found in many commercial applications. The Beliefs, Desires and Intention (BDI) agent architecture is probably the most mature model for many industrial applications in today’s context. However, it is not the best agent model for complex applications that must learn and adapt their behaviours in making rational decisions. We propose a new hybrid BDI framework with an intelligent module to overcome the limitations in the generic BDI model. Learning and the adaptability of the environments are assured with the introduction of the Knowledge Acquisition Module (KAM) in the generic BDI architecture in our proposed framework. The dynamic selection of the intention structures has been improved with a trained neural network. The knowledge required to handle vagueness or uncertainty in the environment has been modelled with an Adaptive Neuro Fuzzy Inference System (ANFIS) in berths. Finally, the benefits and the usability of hybrid BDI model for a vessel berthing application is discussed with experiential results.     

Identification of a company’s suitability for the adoption of cloud computing and modelling its corresponding Return on Investment

Internet has become pervasive in our daily life and cloud computing is the newest offering as service over the ubiquitous Web. Cloud computing has been considered as a much hyped phenomenon in the IT and business world promising to deliver a host of benefits. Companies need to look beyond this hype and seriously consider the real value of incorporating the Cloud in their own businesses. This paper is aimed at helping companies analyze several characteristics of their own business as well as pre-existing IT resources to identify their favorability in the migration to the Cloud Architecture. A general Return on Investment (ROI) model has also been developed here taking into consideration various intangible impacts of Cloud Computing, apart from the cost. The analysis presented herein provides a much broader perspective and insight into Cloud Computing to its prospective adopters.     

Fuzzy resource management analysis

Traditionally, the efficient and productive delivery of services is a major goal of public institutions. This is especially true in the law enforcement industry. Here, the management of a set of dynamic resources (police patrol personnel) is central to the delivery of services. In the past there have been two major perspectives towards the management of low enforcement resources: first, ignoring all patterns in demands resources are distributed equally across time and space. Second, resources are deployed according to the proportionate distribution of demands. In both of these models the resources are manipulated or controlled according to an algorithm derived independently from demand patterns. These models are highly vulnerable to shifts in demand patterns and can be strategically inefficient and tactically unstable. In this paper a new algorithmic process is defined for the strategic and tactical evaluation of resource needs for police patrolling which combines deployment and control strategies, and simulates combinations of the strategies for comparative analysis. It was discovered that the degree of reliance upon the analysis of future resource usage and the accuracy of the projection of the future demands had a significant impact on the performance of the methodologies studied. This process can be used to draw general conclusions about patrolling systems.     

A class of multilevel recursive incomplete LU preconditioning techniques

We introduce a class of multilevel recursive incomplete LU preconditioning techniques (RILUM) for solving general sparse matrices. This technique is based on a recursive two by two block incomplete LU factorization on the coefficient matrix. The coarse level system is constructed as an (approximate) Schur complement. A dynamic preconditioner is obtained by solving the Schur complement matrix approximately. The novelty of the proposed techniques is to solve the Schur complement matrix by a preconditioned Krylov subspace method. Such a reduction process is repeated to yield a multilevel recursive preconditioner.