Shortlisting procedure with a limited capacity

A decision maker, who is overwhelmed by the number of available alternatives, limits her consideration. We investigate a model where a decision maker’s capacity determines whether she is overwhelmed: She considers all the available alternatives if their number does not exceed her capacity; otherwise, she applies a shortlisting procedure to reduce the number of alternatives to within her capacity. We show how to deduce the decision maker’s capacity, her preference and the alternatives that she considers from the observed behavior. Furthermore, we provide the necessary and sufficient conditions for a consideration function to be derived by the shortlisting procedure with a limited capacity.     

Similarity-based mistakes in choice

We characterize the following choice procedure. The decision maker is endowed with two binary relations over alternatives, a preference and a similarity. In every choice problem she includes in her choice set all alternatives which are similar to the best feasible alternative. Hence she can, by mistake, choose an inferior option because it is similar to the best. We characterize this boundedly rational behavior by suitably weakening the rationalizability axiom of Arrow (1959). We also characterize a variation where the decision maker chooses alternatives on the basis of their similarities to attractive yet infeasible options. We show that similarity-based mistakes of either kind lead to cyclical behavior. Finally, we reinterpret our procedure as a method for choosing a bundle given a set of individual items, in which the decision maker combines the best feasible item with those that complement it.     

Increasing sales by introducing non‐salable items

Rationality implies that adding ‘irrelevant’ and, in particular, inferior alternatives to the opportunity set cannot increase the choice probability of some other alternative. In this study, we propose a novel approach that can rationalize an intended addition of such alternatives because it strictly increases the choice probability of some existing alternative. The driving force behind the existence and extent of such an increase is the random nature of individual preferences, that implies intransitivity, and the random nature of the applied choice procedures. We study the case of a firm interested in increasing the sales of some of its existing products by introducing a new and inferior (non‐salable) product. Our main results focus on the feasibility and potential advantage of a successful such strategy. We first establish necessary and sufficient conditions for an increase in the sale probability and then derive the maximal possible absolute and relative increase in this probability, when the firm has extremely limited information on the characteristics of the consumers. We then derive analogous results, assuming that the existing line of products consists of just two items and that the firm has accurate information on the consumers' stochastic preferences over the existing products. These later results are illustrated using some experimental evidence. The applicability of the approach is finally briefly discussed in the context of branding policy. Copyright © 2006 John Wiley & Sons, Ltd.     

Mapping verbal responses to numerical scales in the analytic hierarchy process

Central to the analytic hierarchy process (AHP) are the pairwise comparisons between decision alternatives that are elicited either verbally or numerically. Since comparisons expressed in numbers are required to compute importance weights in the approach, all verbal judgments must be quantified. We propose new scales, and develop a way to identify which numerical scale is best for a given individual. The approach is based on newly-designed compound operation of decision-makers’ preference judgments. We illustrate this process with two examples.     

Unconscious bias in the HRM literature: Towards a critical-reflexive approach

This article presents a systematic review of the human resource management (HRM) literature to document how the term “unconscious bias” is defined, theorized, and operationalized in a sample of 518 articles in the field. The review identifies four main thematic streams in which unconscious bias is commonly discussed: (1) the biased individual; (2) bias as binary; (3) bias in moments of decisions; and (4) bias as a fixable issue. Based on this thematic mapping of the literature, a critical-reflexive approach is outlined to shed light on and challenge taken-for-granted assumptions, interrogate how arguments are brought forth and open up new avenues for future research. This article contributes to the existing HRM literature in three ways. First, it shows patterns in existing theory, making explicit the inconsistencies and tacit assumptions in the ways in which unconscious bias is theorized in HRM research. Second, it presents a critical-reflexive approach to researching unconscious bias. Third, based on this approach, it suggests avenues for future research on how to move beyond these inconsistencies and assumptions.     

Fuzzy multi-linguistic preferences model of service innovations at wholesale service delivery

In group decision making, most researches often assume the linguistic ways with personal preferences have been given and ignore the linguistic evaluated formats involving their knowledge and experience. In practice, people contributing to the judgment tend generally to give ratings about their personal preferences depending on their background. Thus, problems in multiple linguistic preferences go undetected, resulting in the evaluation process not satisfying with decisions’ expectations. In this study, we provide a fuzzy multiple preference integrated model with two stages to better reduce the bias for group decision makings. The first stage focuses on making the information unify on the alternatives according to the individual linguistic preferences, then we compute collective performance values and solve the problems lacking on the integration of respective fuzzy choice subsets. The second stage, we choose the alternatives of retailing service innovations according to the collective performance values by stage one. The goal of the decision process is to reach the subjective fuzzy cognitions in terms of the preference values of all the decision makers. Finally, the survey data of the chain wholesale using multiple preference formats in service innovations determination is verified.     

Acquisition Strategy and Dominant Logic in an Engineering Firm

This paper presents a dynamic model of acquisition strategy and applies it to the case history of a large engineering firm. The paper uses the notion of 'dominant logic' first put forward by Prahalad and Bettis (1986) to explain how the firm's acquisition strategy and management approach evolved. It is suggested that the core activities and history of the firm led to the development of a management approach that emphasized individual autonomy and development, ad hoc structural arrangements, a short-term focus, and flexibility and opportunism. These characteristics persisted over time and tended to inhibit both commitment to intended strategies and extension of core competencies. At the same time, this logic encouraged opportunistic acquisitions which snowballed into a major new strategic thrust. It is concluded: (a) the firm's 'dominant logic' rooted in core activities and in the history of a firm can be used to explain its acquisition management behaviour; (b) the more malleable elements of a dominant logic can be somewhat extended under the thrust of key managers, but permanent change will not occur as long as these shifts conflict with more immutable elements; (c) in a process of growth by acquisition, a firm will tend to preserve its unique dominant logic until the inconsistencies it creates are revealed in a crisis or series of crises. One mode of adjustment may then be to operate under more than one dominant logic to accommodate the firm's heterogeneity.     

一种基于模糊距离和证据理论的多属性群决策方法

针对语言评价信息形式的多属性群决策问题,提出了一种基于模糊距离和D-S证据理论的群决策方法。该方法首先运用基于模糊距离的方法来获得决策者权重,再对多个决策者给出的语言评价信息进行分析,然后通过D-S合成法则对其值进行合成。计算信度函数和似真函数,据此对所有决策方案进行排序。最后通过一个算例验证该方法的可行性和有效性。     

Assessment of Consumer Behavior Towards Environmental Responsibility: A Structural Equations Modeling Approach

This paper analyses the factors impacting consumer environmental responsibility using a structural equation modeling approach. Consumer environmental responsibility is the intention of a person to act towards remediation of environmental problems not as an individual user with economic interests but as a responsible citizen having concerns about the social and environmental wellbeing of society. Therefore, awareness of environmental problems and knowledge of remedial alternatives will help individuals to pursue their chosen action and bolster a genuine desire to act and determine the measures for alleviation of environmental challenges. The four dimensions of an environmentally responsible consumer – opinion and beliefs, willingness, awareness, and an ability to act – are analysed. During the analysis, the dimension of ‘ability to move’ is found to be critical, because it has a direct influence on the capacity of the consumer to act. This research is intended to guide policy‐ and decision‐makers of regulatory bodies in understanding consumer behavior towards improving environmental performance index. It also helps organizational managers to make their supply chains green, and competitive, which in turn improves brand image and overall organizational performance. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

Individual adoption of HR analytics: a fine grained view of the early stages leading to adoption

Abstract

High performing organizations are using analytics for evidence-based decision-making. However, the human resource (HR) function in many organizations has been slow to adopt this innovation. This study applies innovation theory, informed by the Theory of Planned Behavior (TPB), to examine the individual’s decision to adopt HR Analytics in an effort to identify why the adoption rate is lagging. We examined early stages of the individual decision process beginning from Stage 1 (knowledge) and leading to Stage 3, (the decision) to adopt or not to adopt the innovation. We found several points in the process that can act as barriers or facilitators. Organizations and champions of this innovation wishing to facilitate HR analytics adoption can take action to remove as many of these barriers to the individual’s decision as possible. Further research should focus on the best way to remove these barriers.     

Estimating causal effects of credit decisions

In principle, making credit decisions under uncertainty can be approached by estimating the potential future outcomes that will result from the various decision alternatives. In practice, estimation difficulties may arise as a result of selection bias and limited historic testing. We review some theoretical results and practical estimation tools from observation study design and causal modeling, and evaluate their relevance to credit decision problems. Building on these results and tools, we propose a novel approach for estimating potential outcomes for credit decisions with multiple alternatives based on matching on multiple propensity scores. We demonstrate the approach and discuss results for risk-based pricing and credit line increase problems. Among the strengths of our approach are its transparency about data support for the estimates and its ability to incorporate prior knowledge in the extrapolative inference of treatment-response curves.     

The structure of decision schemes with cardinal preferences

This paper replacesGibbard’s (Econometrica 45:665-681, 1977) assumption of strict ordinal preferences by themore natural assumption of cardinal preferences on the set pure social alternatives and we also admit indifferences among the alternatives. By following a similar line of reasoning to the Gibbard-Satterthwaite theoremin the deterministic framework, we first show that if a decision scheme satisfies strategy proofness and unanimity, then there is an underlying probabilistic neutrality result which generates an additive coalitional power function. This result is then used to prove that a decision scheme which satisfies strategy proofness and unanimity can be represented as a weak random dictatorship. A weak random dictatorship assigns each individual a chance to be a weak dictator. An individual has weak dictatorial power if the support of the social choice lottery is always a subset of his/her maximal utility set. In contrast to Gibbard’s complete characterization of randomdictatorship, we also demonstrate with an example that strategy proofness and unanimity are sufficient but not necessary conditions for a weak random dictatorship.     

A decision‐analytic approach to screening in chemical alternatives assessment

Material selection in the chemistry value chain involves consideration of many objectives, including cost, performance, health risk, and environmental impact. Alternatives assessment is an emerging tool for guiding complex decisions with respect to these goals. As a relatively new method, the process is not yet well developed, especially with respect to how trade‐offs among objectives can be assessed accurately and inexpensively. Using paint strippers alternatives assessment as an illustrative example, we show how an established decision‐analytic method, known as comparative screening, allows for a multistep process with gradually increasing information needs. Compared with existing methodological approaches, comparative screening instills flexible and consistent treatment of trade‐offs. This is important because it maximizes the potential for a robust assessment while minimizing arduous data collection. Further, its use in the alternatives assessment process can support the selection of more sustainable materials.     

EVALUATING ALTERNATIVE REPRESENTATIONS OF THE CHOICE SETS IN MODELS OF LABOR SUPPLY

Abstract.  During the last two decades, the discrete choice modeling of labor supply decisions has become increasingly popular. Within the literature adopting this approach, however, there are two potentially important issues that so far have not been given the attention they might deserve. A first issue concerns the procedure by which the discrete alternatives are selected to enter the choice set. Most authors choose (not probabilistically) a set of fixed points identical for every individual. Some authors adopt instead a sampling procedure and also assume that the choice set may differ across households. A second issue concerns the availability of the alternatives. Most authors assume all the values of hours of work within some range are equally available. At the other extreme, some authors assume only two or three alternatives (for example, nonparticipation, part-time and full-time) are available for everyone. Some studies account instead for the fact that not all the hour opportunities are equally available to everyone specifying a probability density function of opportunities for each individual. In this paper we explore by simulation the implications of (i) the procedure used to build the choice set (fixed alternatives versus sampled alternatives); (ii) accounting or not accounting for a different availability of alternatives. The results of the evaluation performed in this paper show that the way the choice set is represented has little impact on the fitting of observed values, but a more significant and important impact on the out-of-sample prediction performance. Thus, the treatment of the choice sets might have a crucial effect on the result of policy evaluations.     

Stratified network mapping decision making technique based decision support framework for R&D budget allocation in South Korea

In this research work, we proposed and developed a stratified network mapping (SNM) decision making method and used it to improve the industry–university specialization in R&D in each region selected in this study. The proposed method considers the influence of criteria on and their priority in alternatives performance evaluation process. By analyzing the influence of these criteria on decision-making, we can easily improve the performance of alternatives. The SNM gives a clear understanding of each alternatives performance efficiency level. It explores possible and inefficient states and high-level influence states in inefficient states. Narrowly using multi-criteria decision-making methods to rank alternatives does not improve the performance of alternatives. The proposed method helps rank alternatives and improve the performance level of alternatives in each state. We analyzed the R&D investment of central and local governments of South Korea. It is an attempt to invigorate and facilitate R&D collaboration using a decision support model. We analyzed industry–academia research networks and enhanced the efficiency of the research.     

Risky business: The role of risk in voluntary turnover decisions

One aspect of turnover decision-making that turnover models have not adequately considered is the risk associated with quitting one's job and the potential that research on risky decision-making has for advancing understanding of turnover. We define risk and present turnover as a risky decision; review previous applications of risk in turnover theory; review literature on decision-making under risk as it applies to turnover; integrate these literatures and provide propositions. Our analysis suggests that individual differences, frames of reference, the decision context, and social influences affect perceptions of the risk associated with quitting as well as the willingness to take risks in this particular situation. The implications of turnover risk perceptions and turnover risk propensity for turnover theory and research are discussed.     

A fuzzy AHP approach based on the concept of possibility extent

The main purpose of this paper is to develop a fuzzy AHP method for tackling the uncertainty and imprecision existing in multi-criteria decision process. The proposed method uses fuzzy pair-wise comparison judgments in place of exact numerical values of the comparison ratios. The geometric mean technique is used to integrate all decision-makers’ opinions and construct the fuzzy positive reciprocal matrices. The algebraic operations of triangular fuzzy numbers are utilized to calculate the fuzzy suitability indices of all alternatives. The extent analysis method is used to compute the degree of possibility of priority among fuzzy suitability indices. Besides, two principles are presented to solve the multi-criteria decision problem in a fuzzy decision environment. Principle I provides a partial preorder, and Principle II gives a total preorder on the set of the possible alternatives. Finally, a numerical example of selecting the company with optimal performance in performing customer relationship management is used to demonstrate the decision process of proposed method.     

Decision-making under uncertainty for capital budgeting and hiring

Most business decisions are not merely risky but are subject to uncertainty. Different individuals estimate different measures of merit. It is shown that the traditional procedure of ranking the alternatives by their estimated measure of merit and then choosing the highest ranked alternative frequently gives the wrong answer even where the estimates are unbiased. The argument will be made using a simple decision tree. The effect will be shown to be especially serious where there is competition, direct or indirect, between the alternatives.     

Optimal Portfolio Choice Under Decision‐Based Model Combinations

We propose a density combination approach featuring combination weights that depend on the past forecast performance of the individual models entering the combination through a utility‐based objective function. We apply this model combination scheme to forecast stock returns, both at the aggregate level and by industry, and investigate its forecasting performance relative to a host of existing combination methods, both within the class of linear and time‐varying coefficients, stochastic volatility models. Overall, we find that our combination scheme produces markedly more accurate predictions than the existing alternatives, both in terms of statistical and economic measures of out‐of‐sample predictability. Copyright © 2016 John Wiley & Sons, Ltd.