Making tough choices: A policy capturing approach to evaluating the tradeoffs in sustainable supplier development initiatives

This research explores the tradeoffs that decision makers are willing to make when implementing development initiatives to improve supplier sustainability performance. We employ a policy capturing methodology in which respondents are forced to choose between multiple potential sustainable supplier development initiatives. Data were collected from traditional and executive MBA students. The results suggest that when confronted with tradeoffs, decision makers value improvements in supplier cost savings and injury reduction equally, which was somewhat unexpected. Further, both improvements in supplier cost savings and injury reduction were valued over supplier emissions performance. Because we measure individual tradeoff preferences, multi-level regression analysis was used to better understand the impact of respondent value structure regarding sustainably developing suppliers. Our findings suggest a hierarchy of tradeoff preferences for decision makers as they pertain to sustainable supplier development. As the pressure to ensure supply chain sustainability increases, more firms will engage in sustainable supplier development. The outcomes of the choices they make when choosing between initiatives, and how managers make these choices, will be of increasing interest in both industry and academia. This research answers previous calls for further examination of decision maker tradeoff preferences in sustainable supply chain development.     

Economics,economists, and public policy☆

This article examines the role of economics and economists in shaping public policy by, first, examining the employment of economists in government, academe, and the private sector. In the United States, only a minority of Ph.D. economists (about 12 percent) are employed in government, and several important departments of the federal government employ few economists. The article goes on to illustrate the pitfalls that economists face in assisting and advising with public policy by examining the adoption of statistical profiling in Unemployment Insurance. The article concludes that, if the economics profession and economic research are to be effective in shaping public policy, then academic economists must become more directly involved with policy makers in government and decision makers in business.     

Macroeconomies as constructively rational games

Real-world decision-makers are forced to be locally constructive; that is, their decisions are necessarily constrained by their interaction networks, information, beliefs, and physical states. This study transforms an otherwise standard dynamic macroeconomic model into an open-ended dynamic game by requiring consumers and firms with intertemporal utility and profit objectives to be locally constructive. Tested locally constructive decision processes for the consumers and firms range from simple reactive reinforcement learning to adaptive dynamic programming (ADP). Computational experiments are used to explore macroeconomic performance under alternative decision-process combinations relative to a social planner benchmark solution. A key finding is that simpler decision processes can outperform more sophisticated decision processes such as ADP. However, memory length permitting some degree of adaptive foresight is critical for good performance.     

A dialectical theory of the decision to go to work: Bringing together absenteeism and presenteeism

The decision to not attend work (absenteeism) has been the focus of a great deal of inquiry; however, research is emerging on the importance of the decision to attend work when ill (presenteeism). Interestingly, despite being the outcome of the same decision, these constructs have developed relatively independently. We argue that absenteeism and presenteeism are strategies employees use to navigate the dialectical tensions in the supervisor–subordinate relationship. Thus, understanding the nature of those tensions, their context, and the strategies employed to manage the tensions can inform employees' decision to attend work.     

Decision making in the beer game and supply chain performance

The beer game has been used to emphasize, investigate, and analyze supply chain inefficiencies as well as the effect of decision makers’ biases. This paper investigates the short- and long-run performance in the beer distribution game by analyzing Sterman’s (Manag Sci 35(3): 321–339, 1989) model that simulates decision-making. In this model, the system may have chaotic behavior depending on the heuristics used by decision makers. We investigate how quickly the system reaches a steady state (if at all). It is known that ignoring supply line (outstanding orders) leads to the bullwhip effect in experimental research. Among other results, we show that the short-term performance of a supply chain is not a predictor of the long-term performance even when decision makers fully recognize outstanding orders. Results of the simulation and practical implications are discussed.     

Bracing for demand shocks: An experimental investigation

We investigate inventory ordering decisions when decision makers anticipated a demand shock. Decision makers anticipating an event have been shown to brace for an uncertain negative outcome by overestimating the likelihood of that event. Decision makers faced with a spike in demand may incur increased holding costs because they may brace, exhibiting a judgment bias, and consequently a decision bias by over-ordering inventory. Three studies span conditions of uncertainty regarding the timing and magnitude of a demand shock: Employing three between-subjects experiments, Study 1 investigates behavior when decision makers were faced with uncertainty in timing and in magnitude of demand at the most elemental level, manipulating holding and stock out costs. The three experimental tasks feature uncertainty about the magnitude of demand (Experiment 1.1), uncertainty about the timing of demand (Experiment 1.2), and uncertainty about both the magnitude and timing of demand (Experiment 1.3). Study 2 uses a dynamic, multi-period replenishment task and a between-subjects manipulation regarding the uncertainty of timing and magnitude of a demand shock. Study 3 also employs a multi-period decision environment, but compares behavior under a demand shock condition with that in a condition featuring only random variability. The collective results from the three studies identify a bias toward over-ordering in response to a demand shock, relative to the optimal orders. The between-subjects manipulations in Study 2 points toward a possible remedy as we found that providing information concerning the timing and magnitude of a shock ameliorated the bias. The primary revelation was that decision makers had more difficulty dealing with uncertain timing than with uncertain magnitude of demand. One implication is that it is particularly critical for retailers to carefully plan and manage how they share information with upstream supply chain partners regarding when they plan to introduce store-level promotions.     

Designing awareness campaigns to counter human trafficking: An analytic approach

Human trafficking – the trade of persons for the gain of others – is a pervasive societal issue. Ongoing trafficking recruitment calls for targeted prevention strategies for individuals and communities at risk. Awareness campaigns, arguably the most common form of trafficking prevention, are intended to alert individuals to the tactics used by traffickers and provide them with practical strategies to avoid deception and exploitation. However there is a shortage of technical solutions regarding the analysis, impact assessment, and evaluation of alternatives related to implementing awareness campaigns. We present a resource allocation model that can be used to determine the allocation of funds that maximizes increases in trafficking awareness among at-risk populations. We apply this model to determine the allocation of a limited budget among different types of prevention programs in at-risk populations in Nepal. For each awareness campaign, we estimate a production function that relates the amount invested to the associated change in awareness. When allocating limited resources, decision makers must balance competing interests, and we illustrate the impact of three allocation policies on trafficking awareness. The model presented in this article is a first attempt to help decision makers evaluate how to allocate funds in the context of trafficking awareness.     

Collective decision making by committee

Implicitly or explicitly, economic decisions always contain elements of compromise. However, the bargaining models of economic theory treat only the two decision maker case with linearly aggregated priorities; i.e. compromise decisions under Pareto optimality and no side payments. Even then the relative importance of the decision makers remains indeterminate. This paper proposes a simplified bargaining model with three new features: (a) it allows multiple participants; (b) it uses optimal voting patterns to combine the policy proposals, rather than the policy priorities, to form those compromise decisions; and (c) it determines the relative power of each participant endogenously. Perhaps more important, the method does not depend on each decision maker knowing the preferences of his colleagues exactly.     

Uncertainty perception in bidding for Product-Service Systems under competition

This research investigates what impact of uncertainty perception arising from the existence of competition has on the pricing decision for Product-Service Systems (PSS) under uncertainty. PSS provision is an increasingly important area for many businesses and competition increases cognitive pressures on providers even further. We present an experimental study with industrial costing and bidding experts from the defence and aerospace sector. The study consisted of an experimental set-up via two questionnaires which differed in the existence of competition in the bidding scenario. The findings showed that bidding decision makers changed their evaluation of the cost estimate due to the introduction of competition but kept their evaluations of the profit margin and price bids constant. Furthermore, the participants listed the relevant sources of uncertainty that influenced their decision-making process. This research contributes to the literature in two ways. First, our findings showed that predictions from current theory regarding decision-making of cost estimation and pricing are not confirmed when competitively bidding for PSS. Second, we show uncertainty sources that influenced the decision makers and identified p the importance of internal processes of the PSS provider and environmental uncertainty.     

Business strategic decision making: the role and influence of directors

Drawing on interviews with HR, finance and marketing directors, this article examines the locus of strategic decision making in organisations, who makes those decisions and the characteristics and competencies of strategic decision makers. The article finds that strategic formulation takes place in the Chief Executive Officer Group (CEOG). Board of director membership is unnecessary to be influential on the strategic decisions made in organisations. The article also concludes that even if directors are not members of the main board of directors and/or of the CEOG, there exists in organisations informal channels through which they can exert influence in the formulation of strategy. A third conclusion is that strategic decision makers are business-focused general managers rather than advocates of their management speciality. The article concludes by considering the implications of its findings for management education and for the research agenda and management academics.     

An Empirical Exploration of Decision-making Under Agency Controls and Stewardship Structure

abstract Two theories have emerged in the managerial control literature as to the best way for organizations to ensure that managers are acting in the firm's best interest: agency theory, which stresses controlling decision‐makers through monitoring and incentives aligned with organizational goals, and stewardship theory, which stresses that decision‐makers will act in the organization's best interest even in the absence of controls. Much of the research investigating the utility of these two positions is based on archival data where actual decision‐making can only be inferred. In this study, we utilize a laboratory methodology in order to determine if decision‐makers actually make different decisions when under the types of control (or lack thereof) suggested in these two theories. The results of this study show that individuals under agency controls invest more in alternatives that maximize profits of an organization than individuals under stewardship controls.     

A theory of stochastic choice under uncertainty

In this paper we propose a characterization of stochastic choice under risk and under uncertainty. We presume that decision makers’ actual choices are governed by randomly selected states of mind, and study the representation of decision makers’ perceptions of the stochastic process underlying the selection of their state of mind. The connections of this work to the literatures on random choice, choice behavior when preference are incomplete; choice of menus; and grades of indecisiveness are also discussed.     

Management of a capital stock by Strotz's naive planner

The capital management problem posed by R.H. Strotz is analyzed for the case of the ‘naive’ planner who fails to anticipate changes in his own preferences. By imposing progressively stronger restrictions on the primitives of the problem – namely, the discounting function, the utility index function, and the investment technology – the planner's behavior is characterized first as the solution to an ordinary differential equation and then via explicit formulae. Inasmuch as these characterizations leave the discounting function essentially unrestricted, the theory can accommodate, in particular, decision makers who discount time according to the hyperbolic and ‘quasi-hyperbolic’ curves used in applied work and said to be supported by psychological studies. Comparative statics of the model are discussed, as are extensions of the analysis to allow for credit constraints, limited foresight, and partial commitment.     

Multiperson multitarget decision making,using the versatility criterion

In this paper a model is presented for multicriterion decision making with the objectives in the form of constraints or targets. We assume that the policy alternatives are predetermined, that decision makers are satisficers, and that the values of targets are uncertain. The versatility criterion is used in selecting the feasible policy which maximizes the probability of attaining the objectives. Different assumptions concerning the distribution of target values are considered. For the case of a multivariate normal distribution an algorithm is outlined which uses the Monte Carlo method for numerical integration. A simple example illustrates the potential use of the model when there is a large number of decision makers with different objectives.     

Optimal dividend strategies with time-inconsistent preferences

This paper studies the optimal dividend strategies of an insurance company when the manager has time-inconsistent preferences. We consider the problem for a naive manager and a sophisticated manager, and analytically derive the optimal dividend strategies when claim sizes follow an exponential distribution. Our results show that the manager with time-inconsistent preferences tends to pay out dividends earlier than her time-consistent counterpart and that the sophisticated manager is more inclined to pay out dividends than the naive manager. Furthermore, we extend these results to the case with claim sizes following a mixed exponential distribution, and provide a numerical analysis to reveal the sensitivity of the optimal dividend strategies to changes in the premium, claims and surplus volatility.     

Green supplier selection: a new genetic/immune strategy with industrial application

With the onset of the ‘climate change movement’, organisations are striving to include environmental criteria into the supplier selection process. This article hybridises a Green Data Envelopment Analysis (GDEA)-based approach with a new Genetic/Immune Strategy for Data Envelopment Analysis (GIS-DEA). A GIS-DEA approach provides a different view to solving multi-criteria decision making problems using data envelopment analysis (DEA) by considering DEA as a multi-objective optimisation problem with efficiency as one objective and proximity of solution to decision makers’ preferences as the other objective. The hybrid approach called GIS-GDEA is applied here to a well-known automobile spare parts manufacturer in India and the results presented. User validation developed based on specific set of criteria suggests that the supplier selection process with GIS-GDEA is more practical than other approaches in a current industrial scenario with multiple decision makers.     

Global supplier selection using fuzzy analytic hierarchy process and fuzzy goal programming

Global supplier selection is a multi-goal multi-criteria problem which needs to consider both qualitative and quantitative factors. Which suppliers are the best and how much should be purchased from the selected suppliers is an important purchasing issue for manufacturers. Traditionally, decision makers can determine the best supplier from evaluating few suppliers with qualitative supplier selection criteria by using fuzzy analytic hierarchy process (FAHP), but evaluate dozens of global suppliers simultaneously or determine the order quantity from them will be complex and difficult. Meanwhile, decision makers can determine the order quantity form the suitable suppliers by using fuzzy goal programming (FGP); however, it is not easy to decide weights for each goal of global supplier selection with different supply chain strategies. This study integrated the FAHP and FGP (FAHP-FGP) method to be a new approach for global supplier selection in considering the manufacturer’s supply chain strategies. With FAHP-FGP method, the manufacturer can consistently integrate multi-manager’ opinions in determining weights of each goal and obtain the order quantities for suitable suppliers based on manufacturer’s strategies. To demonstrate the usefulness of the proposed method, a real-world case of a digital consumer products manufacturer is presented.