Janus and the Delphi Oracle: Entering the new world of international business research

Globalization and other dramatic, world-changing developments have all too frequently taken academic researchers by surprise. Within this dynamic, turbulent environment, international business (IB) researchers must comprehend increasingly complex, multicultural, cross-border activities and organizing systems while providing relevant results to the field. To build and sustain relevance, the international research paradigm must expand to incorporate not only the analysis of historical trends and events but also research frameworks and methods geared to investigation of the future. With this expanded research ‘tool kit’, we will be better able to anticipate and address the ‘Big Questions’ confronting global business operations in the twenty-first century.This paper examines the capabilities of the Delphi Method of scientific inquiry as one such tool which is responsive to the challenging demands of our discipline and describes recent innovations that enhance the Delphi's application to international management research. As this paper demonstrates, the Delphi Method is particularly well-suited to emerging research themes that call on IB researchers to interpret intricate sets of entities, activities, and relationships. Based on conclusions drawn from a summary of recent Delphi studies, recommendations are offered for maximizing the benefits of this method for international research.     

Behavioural aspects of marketing information systems

A survey of 84 users of marketing information systems in 33 companies was conducted to determine the relationship between usage of their systems and (i) attitude factors, (ii) perceived organizational factors, (iii) personality dimensions. Principal components analysis was used to derive underlying attitude and organizational factors as measured by responses to a series of statements derived from exploratory research. Personality was measured by means of the Eysenck Personality Inventory. Usage of the system was measured by seven usage variables constructed to capture the various dimensions of usage identified at the exploratory stage of the research. A series of multiple regressions were used to relate the criterion variables (usage dimensions) to each of the predictor variables (attitude factors, perceived organizational factors, and personality). A number of attitude factors, and perceived organizational factors was found to be significantly related to usage. In the main, personality was not related to usage. The results support earlier research in the USA which indicate association between attitudes and usage, and point to the importance of researching organizational aspects which may affect usage. A number of specific features of marketing information systems design is supported by the results of this study. The paper, therefore, provides an analysis of a wider number of factors which may be related to use than earlier studies, provides statistical support for a number of design issues, relates American findings to British experience and is based upon a larger and more comprehensive sample than previous research.     

A Delphi Method Expert Survey to Derive Standards for Flood Damage Data Collection

For the purpose of flood damage analyses reliable, comparable, comprehensive, consistent, and up-to-date data are an indispensable need. Like in many other countries a database with this kind of datasets does not exist in Germany. To establish it, standards have to be set for flood damage data collection. We approached this problem by questioning experts about their information needs for flood damage analysis. This survey is done by applying a Delphi survey approach. The aptitude of the Delphi approach to assess, structure, and standardize expert knowledge is evaluated in this article. In the survey a panel of 55 experts working in the field of flood damage analysis for insurances, engineering companies/consultancy, public water management, and universities and other scientific institutions helped to identify common information needs. The multi-step Delphi method proved to reduce the deviation of answers thereby enabling consensual results and also enhanced the quality by modifying group answers in the direction of experience based answers. There was also a high level of congruence in information needs between experts from different fields of employment that allowed the derivation of common standards.     

The Delphi method and urbanization

In this article the author puts forward his reasons for wishing to use the Delphi method for a future forecasting programme in Canada. He argues that the results of such a survey should be of great assistance in the field of urban affairs.     

基于区间数证据推理方法的用户满意度调查

目前,加权平均法是一种比较常见的满意度调查结果的汇总方法,但是这种方法的前提条件是决策者的偏好结构满足加性独立条件,否则需要采用非线性综合方法。本文旨在考虑决策者偏好不满足加性独立条件下,将用户满意度抽样调查过程中产生的置信度和置信区间与调查问卷中的用户不确定的评价结果统一进行考虑,并采用mass函数值为区间数的证据推理方法分析基于抽样调查得到的以置信区间表示的用户满意度调查的结果综合问题。最后以某网络信息中心用户满意度调查为例展开实证分析。     

A unique event and Delphi

In this article the author describes the application of a Delphi forecast in response to a unique event—The Stockton & Darlington Railway Anniversary 1975. He illustrates the successes and failures of the survey and makes recommendations as to how failures may have been avoided. The article also includes ideas on how the Delphi approach might be used in other ways in social forecasting.     

Guidelines for Improving the Power Values of Statistical Tests for Nonresponse Bias Assessment in OM Research

The assessment of nonresponse bias in survey‐based empirical studies plays an important role in establishing the credibility of research results. Statistical methods that involve the comparison of responses from two groups (e.g., early vs. late respondents) on multiple characteristics, which are relevant to the study, are frequently utilized in the assessment of nonresponse bias. We consider the concepts of individual and complete statistical power used for multiple testing and show their relevance for determining the number of statistical tests to perform when assessing nonresponse bias. Our analysis of factors that influence both individual and complete power levels, yielded recommendations that can be used by operations management (OM) empirical researchers to improve their assessment of nonresponse bias. A power analysis of 61 survey‐based research papers published in three prestigious academic operations management journals, over the last decade, showed the occurrence of very low (<0.4) power levels in some of the statistical tests used for assessing nonresponse bias. Such low power levels can lead to erroneous conclusions about nonresponse bias, and are indicators of the need for more rigor in the assessment of nonresponse bias in OM research.     

Using Cognitive Mapping in Management Research: Decisions about Technical Innovation

Case studies of firms attempting to adopt a particular type of technological innovation have demonstrated that the process of technological innovation may be mediated by decision-makers' access to knowledge and by their cognitions—reflected in belief systems. This paper highlights the importance of cognitions in decisions about technological innovation. However, cognitive processes have been under emphasized in empirical work on technological innovation and part of the problem may have been lack of availability of research tools and techniques with which to explore cognitions. Cognitive mapping methodologies are reviewed in terms of their potential to fill this gap in the research into technological innovation. The paper discusses these methodologies, evaluates their limitations and argues that a distinction should be made between cognitive maps and the output of mapping techniques. This paper concludes that cognitive mapping may provide a useful addition to existing management research tools provided researchers are clear about what is revealed by the particular methodology used.     

Pooling Data Across Transparently Different Groups of Key Informants: Measurement Equivalence and Survey Research*

Survey research is often deployed in the study of situational issues facing organizations and functions within organizations. One particular survey research approach can be described as follows: (1) survey questionnaires involving perceptual questions about a situational issue are administered to key informants, one key informant per unit of analysis; (2) key informants vary in a transparent manner across units of analysis such that groups of these key informants are discernible; and (3) perceptual responses, after data collection, are then pooled to create a single larger data set for subsequent statistical manipulations. In this methodological note, we draw attention to this particular survey research approach and ask the question: When is it appropriate to pool data provided by key informants with transparently different demographics across units of analysis so as to create a single larger data set for statistical manipulations? We use a simple example and data from a published study to motivate the relevance and gravity of this methodological question. Offering the concept and empirical assessment of measurement equivalence as the answer to this methodological question of data pooling, we prescribe and demonstrate, with the total quality management→customer satisfaction relationship, the procedural steps for evaluating the seven subdimensions of measurement equivalence. In conclusion, we highlight methods that should be adopted, before data collection, to minimize the risk of violating measurement equivalence. After data collection and for the instances when the empirical assessment for measurement equivalence advises against pooling of such data, we also offer suggestions for analyzing such data and presenting associated statistical results.     

Long range planning in Bell Canada

The objectives and activities of Bell Canada's Business Planning group are outlined. The Business Planning process of obtaining inputs, organizing the data base, and creating outputs is elaborated. Inputs are derived from original research efforts such as trend extrapolation, Delphi research and survey research. Selected results from Business Planning studies are illustrated. Inputs obtained through secondary research activities are also outlined. The creation of a key-word-indexed on-line information retrieval system to organize the data base is described. The underlying group philosophy of developing outputs that support and/or stimulate the executive decision making process is stressed in the development of Business Planning Outputs.     

An opportunity for system dynamics in manufacturing system modelling

The computer simulation of manufacturing systems is commonly carried out using discrete event simulation (DES). Indeed, there appears to be a lack of applications of continuous simulation methods, particularly system dynamics (SD), despite evidence that this technique is suitable for industrial modelling. This paper investigates whether this is due to a decline in the general popularity of SD, or whether modelling of manufacturing systems represents a missed opportunity for SD. On this basis, the paper first gives a review of the concept of SD and fully describes the modelling technique. Following on, a survey of the published applications of SD in the 1990s is made by developing and using a structured classification approach. From this review, observations are made about the application of the SD method and opportunities for future research are suggested.     

Lot-sizing decisions under limited-time price incentives: A review

The problem of determining the optimal order quantities for an inventoried item, when the vendor offers a limited-time price reduction is both interesting and important. It is interesting in that it has received continued attention of academic researchers for over four decades and it is important given its economic implication in a variety of practical settings. The extensive literature on this problem represents a fascinating confluence of: (1) economic significance and relevance to managerial practice, (2) continuing academic research interest directed at precise mathematical analysis leading to the development of rigorous and complex models and policies, and (3) elegance and adequacy of simple models and heuristic policies which are validated by the results of rigorous models and computational analysis. In this paper, we survey this literature using simple classification frameworks and then review some of the key studies. We highlight their key assumptions and findings, bring across key implications for policy implementation and academic research and identify avenues for further research.     

Production System Development for Expert Systems Using a Recursive Partitioning Induction Approach: An Application to Mortgage,Commercial, and Consumer Lending

The concepts of expert systems and decision support systems have received considerable attention recently. While systems have been proposed for various problem areas in business, difficulties still exist in the knowledge acquisition phase of development. This paper presents a recursive partitioning analysis (RPA) approach to knowledge acquisition. The RPA production system approach was applied to data sets representing the mortgage, commercial, and consumer lending problems. Comparison of the classification rates across these problems to the results of a generalized inductive inference production system (Quinlan's ID3 algorithm) and across the mortgage and commercial lending problems to traditional statistical modeling approaches indicated that the RPA approach provided superior results while using fewer variables.     

An integrated survey of deterministic project scheduling

There have been many survey papers in the area of project scheduling in recent years. These papers have primarily emphasized modeling and algorithmic contributions for specific classes of project scheduling problems, such as net present value (NPV) maximization and makespan minimization, with and without resource constraints. Paralleling these developments has been the research in the area of project scheduling decision support, with its emphasis on data sets, data generation methods, and so on, that are essential to benchmark, evaluate, and compare the new models, algorithms and heuristic techniques. These investigations have extended the frontiers of research and application in all areas of project scheduling and management. In this paper, we survey the vast literature in this area with a perspective that integrates models, data, and optimal and heuristic algorithms, for the major classes of project scheduling problems. We also include recent surveys that have compared commercial project scheduling systems. Finally, we present an overview of web-based decision support systems and discuss the potential of this technology in enabling and facilitating researchers and practitioners in identifying new areas of inquiry and application.     

A NEW LEARNING APPROACH TO PROCESS IMPROVEMENT IN A TELECOMMUNICATIONS COMPANY

Redesigning and improving business processes to better serve customer needs has become a priority in service industries as they scramble to become more competitive. We describe an approach to process improvement that is being developed collaboratively by applied researchers at US WEST, a major telecommunications company, and the University of Colorado. Motivated by the need to streamline and to add more quantitative power to traditional quality improvement processes, the new approach uses an artificial intelligence (AI) statistical tree growing method using customer survey data to identify operations areas where improvements are expected to affect customers most. This AI/statistical method also identifies realistic quantitative targets for improvement and suggests specific strategies predicted to have high impart. This research, funded in part by the Colorado Advanced Software Institute (CASI) to stimulate profitable innovations, has resulted in a practical methodology used successfully at US WEST to help set process improvement priorities and guide resource allocation decisions throughout the company.     

Social network and social capital in leadership and management research: A review of causal methods

This paper surveys the methods underlying the burgeoning body of leadership and management research on social networks and social capital (SNSC). A social network is a social structure made up of nodes connected by a set of ties. Social capital, in turn, refers to the structure, content, and perception of one's social relationships in the network. This paper presents an in-depth survey of the methods of using SNSC in leadership and management research. I first review how network scholars determine network boundaries, choose sampling techniques, and collect network data. I follow with a comprehensive survey of the statistical tools and analytical strategies prevalent in SNSC research. I then investigate the methodological rigor of 110 SNSC empirical studies in leadership and other management fields. My results show that 8.1% (3/37) specified network boundaries, 43.2% (49/103) used surveys to collect network data, and 52.3% (58/110) implemented at least one reviewed method. A further assessment reveals that only 39.7% (23/58) of papers somewhat justified the appropriateness of using such methods. The frequency distribution of coding criteria was similar across journals and over time. This review also includes several future research directives for SNSC leadership and management researchers.     

The future of the British breakfast cereals industry

This article discusses the results of a ‘Delphi’ survey undertaken by the author, relating to the U.K. Breakfast Cereals Industry. The effects on this industry of new technologies in production, packaging and distribution functions are here considered together with the likely effects on future sales of: legislation, pricing and advertising policies, quality of product distribution, and rival competition.     

Behavior-based analysis of knowledge dissemination channels in operations management

One essential requirement for the development and vitality of a discipline is a network of channels for knowledge dissemination. These channels, such as scholarly journals, furnish not only a means for knowledge sharing, but also for knowledge generation by the discipline's community of researchers. In the field of operations management (OM), there have been several studies that have sought to rank journals relevant to OM research, using opinion surveys, citation analyses, and author affiliations. However, each of these methods has some limitations. This paper adopts a new approach for discerning journal publication patterns in the OM field. It is based on an examination of the actual publishing behaviors of all full-time, tenured OM researchers at a sizable set of leading research universities in the US. This behavior-based methodology provides three metrics that individually, and in tandem, give a basis for rating publication outlets for OM research in terms of their relative importance. The ratings can be used by scholars and administrators to assist in monitoring, disseminating, and evaluating OM research outlets.     

Planning Implications of the Information Systems Strategic Grid: An Empirical Investigation

In recent years, information systems (IS) planning has come to represent a key IS management tool to practitioners and researchers. Concurrently, there has been increasing recognition by organizations that their IS can be viewed as a strategic resource. This research is an attempt to explore the relationship between these two aspects of IS. It analyzes, in an empirical setting, the contingent nature of some IS planning-related variables in the context of the strategic relevance of an organization's IS. The basis for the empirical test is the IS strategic grid framework developed by Cash, McFarlan, McKenney, and Vitale [6]. A questionnaire survey method is employed to elicit information on the strategic orientation of IS and IS planning issues within respondent organizations. The difference in emphasis on various planning aspects in organizations with different IS environments is analyzed. Results of the analysis indicate that there is empirical support for the strategic grid framework and that there are differences in planning aspects among organizations, depending on their location in the grid. The implications of these findings for IS and IS planning are then discussed.     

Decision Processes for Developing Strategic Applications of Information Systems: A Contingency Approach*

Strategic applications of information systems (IS) are considered by IS researchers to be determined by contextual factors such as environmental uncertainty, and influenced by attributes of the processes preceding them, such as planning and top management support. For better management of the process leading to these applications, it is essential to understand the relationship between process attributes and contextual factors. Utilizing a contingency approach, this article takes a step toward such an understanding. Based on successful strategic IS applications from 81 large companies, it examines the relationship between the context of these applications and the decision-making process leading to them. The results indicate that the external environment is related to whether a rational or political decision-making process is used. The IS function seems to influence the use of the decision process implied by IS researchers, one in which the top management champions the strategic application, while the IS managers contribute by conducting in-depth analysis. However, the organization structure was not related to any decision process attribute. The implications of these findings for future research and practice are also discussed.