Green consumption behavior prediction based on fan-shaped search mechanism fruit fly algorithm optimized neural network

Predicting consumption behavior is very important for adjusting supplier production plans and enterprise marketing activities. Conventional statistical methods are unable to accurately predict green consumption behavior because it is characterized by multivariate nonlinear interactions. The paper proposes an optimized fruit fly algorithm (FOA) and extreme learning machine (ELM) model for consumption behavior prediction. First, to address the problem of uneven search direction of FOA leading to insufficient search ability and low efficiency, the paper proposes a sector search mechanism instead of a random search mechanism to improve the global search ability and convergence speed of FOA. Second, to address the issue that the initial weights and hidden layer bias values of the ELM are randomly generated, which affects the learning efficiency and generalization of the ELM, the paper uses an improved FOA to optimize the weights and bias values of ELM for improving the prediction accuracy. Taking the green vegetable consumption behavior of Beijing residents as an example, the results show the optimization of the initial weight and threshold of ELM by the GA, PSO, FOA, and SFOA, the prediction accuracy of the GA-ELM, PSO-ELM, FOA-ELM, and SFOA-ELM models all surpass those of ELM. Compared with BPNN, GRNN, ELM, GA-ELM, PSO-ELM, and FOA-ELM models, the RMSE value of SFOA-ELM was decreased by 9.45%, 8.40%, 11.89%, 5.84%, 2.22%, and 2.69%, respectively. These findings demonstrate the effectiveness of the SFOA-ELM model in green consumption behavior prediction and provide new ideas for the accurate prediction of consumption behaviors of other green products with similar characteristics.     

Strategic Behavior in Contested-Pile Methods for Fair Division of Indivisible Items

Most fair-division procedures are modeled on cake-cutting procedures such as “I cut, you choose”. The inputs are players’ choices, which are assumed to reflect preferences but not fully reveal them; the output is a division that is in some sense fair. However, it seems likely that decision makers sometimes behave insincerely, that is, they make choices that are not consistent with their true preferences. For example, strategic—as opposed to sincere—behavior may be aimed at taking advantage of information about an opponent’s preferences, which most fair-division procedures assume is not available. We focus on contested-pile procedures, a class of procedures for the fair division of indivisible items between two players, related to the alternation procedures proposed by Brams and Taylor (The win-win solution: guaranteeing fair shares to everybody. W. W. Norton, New York, 1999). We use computational models to assess the performance of these procedures under both sincere and strategic behavior. We show how available information about preferences can interact with strategy to shape outcomes. Our results indicate that strategic behavior, although it often changes outcomes, may not make them less efficient or less fair. Furthermore, our investigation suggests that how information about the opponents preference is processed does not have a strong impact, in that a conceptually simple strategy often outperforms a more elaborate one.     

DUALITY IN OPTIMAL INVESTMENT AND CONSUMPTION PROBLEMS WITH MARKET FRICTIONS

In the style of Rogers (2001) , we give a unified method for finding the dual problem in a given model by stating the problem as an unconstrained Lagrangian problem. In a theoretical part we prove our main theorem, Theorem 3.1, which shows that under a number of conditions the value of the dual and primal problems is equal. The theoretical setting is sufficiently general to be applied to a large number of examples including models with transaction costs, such as Cvitanic and Karatzas (1996) (which could not be covered by the setting in Rogers [2001] ). To apply the general result one has to verify the assumptions of Theorem 3.1 for each concrete example. We show how the method applies for two examples, first Cuoco and Liu (1992) and second Cvitanic and Karatzas (1996) .     

For the Greater Good? A Test for Strategic Bias in Group Environmental Decisions

This paper presents a study which tests for strategic bias in group decision support models. Strategic bias occurs when individuals provide preference information to a group decision model which, they perceive, will improve their own outcomes and not necessarily those of the group. A test is made for strategic bias in a decision model used to allocate funds amongst 14 natural resource management regions in Queensland. The funds are a crucial source of revenue for the regions to achieve environmental objectives. In this real decision problem representatives from each region supplied criteria weights for a multiple criteria analysis model. Results reveal moderate to weak presence of strategic bias. Regions mostly selected weights that would improve their outcome relative to the weights of other regions. But this was not overly pronounced and there were exceptions. Whilst some degree of strategic bias existed these results show a willingness to separate individual and group preferences when interacting with formal decision procedures. Further research is required to see how this changes under unstructured negotiation and arbitration as opposed to a formal model.     

Experiments on strategic choices and markets

Much of experimental research in marketing has focused on individual choices. Yet in many contexts, the outcomes of one’s choices depend on the choices of others. Furthermore, the results obtained in individual decision making context may not be applicable to these strategic choices. In this paper, we discuss three avenues for further advancing our understanding of strategic choices. First, there is a need to develop theories about how people learn to play strategic games. Second, there is an opportunity to enrich standard economic models of strategic behavior by allowing for different types of bounded rationality and by relaxing assumptions about utility formulation. These new models can help us to more accurately predict strategic choices. Finally, future research can improve marketing practice by designing better mechanisms and validating them using experiments.     

Vertical Product Differentiation and Advertising

A duopoly model is developed in which firms' strategic variables include brand quality, the number of distinct market segments to enter and price. Informative advertising is used to overcome consumer ignorance about brands. In contrast to many existing models in which firms engage in price competition, the subgame perfect equilibria of the game are not characterised by the production of vertically differentiated products. Further, whilst the firms typically produce identical high quality products, in some circumstances the production of homogeneous low quality brands can be an equilibrium strategy.     

Rational Strategic Reasoning: An Unnatural Act?

We review recent literature on competitive reactions and strategic thinking and offer several observations. Evidence is mounting that strategic thinking is an unnatural act, made difficult by natural individual biases and organizational roadblocks. In addition, it is possible that uncertainty about competitive behavior is caused by and contributes to informal and incomplete competitive intelligence. We propose a simple model which suggests a potential path dependency in a firm's intelligence gathering, driven by the inertia of its past decision-making. Such a path dependency can be broken, however, as evidenced by several examples of firms who have overcome barriers to strategic thinking in creative ways. Paradoxically, though, there are circumstances in which competition is overemphasized in decision-making. Research priorities are discussed.     

Information Collection Strategic Design in Experts-assisted Decision Making Paradigm

In an experts-assisted decision making paradigm, the information collection design becomes a strategic variable under a weak assumption that the final decision is dependent on the design used to collect information as well. As a result, the same information of the experts and the decision maker about the problem can potentially produce different final decisions for different information collection designs. The implication is that a decision maker can strategically select a design which serves his/her objective. This paper uses a Bayesian estimation methodology for combining experts' information with the decision maker's prior. An information collection process is designed by setting constraints on this model. Several designs are developed here using such controlled factors as a one-stage versus a two-stage decision process, experts' rank ordering, and group versus individual lobbying/consultation. An example is provided to illustrate the applicability of the concept. It is shown that the information produced in the process of producing a decision can also give insights into the impacts of the decision maker and the experts on the decision.     

Strategic orientation and performance measurement model in Taiwan's travel agencies

This longitudinal study attempts to examine those effects and relationships of various performance measuring dimensions using the balanced scorecard conceptual framework on travel agencies under different strategic orientations in Taiwan. A three-stage research design is adopted to explore a valid and reliable e-commerce strategy performance measuring model for travel agencies. The research also uses the structural equation modeling (SEM) approach to further empirically build up e-commerce cost leadership and differentiation strategy performance measurement models. The theoretical model identifies an underlying variable construct, dimensions, and their associated attributes which combine the traditional subjective or objective measures with operating measures of e-commerce strategy performances. According to this research, Taiwanese travel agencies consider five financial, three customer, four internal process, and three innovation and learning perspective indicators of performance measurement that also have cause-and-effect relationships among themselves under two different strategies. Finally, this paper proposes two optimal models that match the essential needs of e-commerce cost leadership and differentiation strategic development and overcomes the traditional performance measuring shortcomings.     

Managing multiple forms of strategic training fit through the Balanced Scorecard

Although the literature recognizes training as an essential driver of organizational effectiveness, little is still known about how to explicitly focus and align training to organizational strategic priorities. This note proposes a model that bridges the strategic human resource management (SHRM) literature and the Balanced Scorecard (BSC) literature – which is one of the most widely recognized strategic performance evaluation approaches intended to foster organizational alignment by translating the firm's strategy into a multidimensional set of financial and non‐financial measures. After having briefly discussed the main differences between the return on investment (ROI) model, which represents one of the major attempt to make training strategic within the existing evaluation research, and the BSC model applied to training management, this note highlights multiple forms of strategic training fit and suggests how to manage training through various scenarios of BSC development. Specifically, the note illustrates four forms of strategic fit – the vertical fit, the horizontal inter‐functional fit, the horizontal intra‐functional fit and the human capital readiness – and discusses their pursuit in terms of six scenarios of training management through the BSC. The note expands some exploratory empirical evidence on the feasibility and usefulness of training scorecards (i.e. the application of the BSC to training) in order to develop some theoretical insights and practical guidance on how they can be leveraged to foster the strategic alignment of training.     

Provision of Step-Level Public Goods with Uncertain Provision Threshold and Continuous Contribution

Common to most theoretical and empirical research on public goods is the assumption that the parameters of the game are common knowledge. Recent theoretical and empirical studies have questioned this assumption by arguing that many public goods situations are characterized by uncertainty regarding various aspects of the situation. In particular, Suleiman (1997) argued that members of production groups of step-level public goods are often uncertain about the value of the provision threshold. For this type of uncertainty he proposed three distinct models to account for the individual's contribution.The present study reports the results of an experiment designed primarily to test and contrast the predictions derived from two of these models – a subjective expected utility model and a cooperative model – regarding the effects of threshold uncertainty on contribution for the provision of step-level public goods. Other goals of the study were to test the joint effect of the threshold uncertainty level, and its mean (low vs. high), on contribution, and to examine the effect of threshold uncertainty on the individuals' estimates regarding the contributions of other group members.The results show that the effect of threshold uncertainty is moderated by the threshold mean: Contribution to the public good increased as a function of uncertainty for the lower threshold mean, and decreased (though not significantly) for the higher threshold mean. In contrast, for the two threshold means the subjects' estimates of the mean and variability of others' contribution increased with threshold uncertainty.The models' comparison revealed that the cooperative model was superior to the subjective expected utility model. This result adds to a substantial body of research on social dilemmas showing that under conditions of social (strategic) uncertainty, group members tacitly coordinate their choice behavior by anchoring their decisions on rules of fairness.     

Improving Service Quality in Person-to-Person Encounters: Integrating Findings from a Multi-disciplinary Review

Although the core of most services is a person-to-person encounter, we still know very little about its underlying mechanisms as very few models or theories have been developed for these dynamic interactions between persons. An holistic approach to quality improvement is therefore suggested. Different prototypical person-to-person encounters may be studied on different levels and interfaces in service operations to eliminate inconsistencies. The aim of this contribution is to review some recent research findings for person-to-person encounters from the neighbouring management fields of services, operations and human resources in order to draw together their strategic implications for service managers. Some ontological and methodological considerations of studying person-to-person encounters from a qualitative perspective are discussed. The outline of a multi-disciplinary and learning-centred research approach is also suggested. Findings are integrated by a model of four generic and strategic processes for quality improvement in service operations. Finally, some implications for managers are proposed.     

Improving Service Quality in Person-to-Person Encounters: Integrating Findings from a Multi-disciplinary Review

Although the core of most services is a person-to-person encounter, we still know very little about its underlying mechanisms as very few models or theories have been developed for these dynamic interactions between persons. An holistic approach to quality improvement is therefore suggested. Different prototypical person-to-person encounters may be studied on different levels and interfaces in service operations to eliminate inconsistencies. The aim of this contribution is to review some recent research findings for person-to-person encounters from the neighbouring management fields of services, operations and human resources in order to draw together their strategic implications for service managers. Some ontological and methodological considerations of studying person-to-person encounters from a qualitative perspective are discussed. The outline of a multi-disciplinary and learning-centred research approach is also suggested. Findings are integrated by a model of four generic and strategic processes for quality improvement in service operations. Finally, some implications for managers are proposed.     

Mitigating panic buying behavior in the epidemic: An evolutionary game perspective

The panic buying behavior under public health emergencies will lead to many adverse consequences, such as material waste, price fluctuation and uneven distribution of epidemic prevention materials, which will pose a threat to the social stability and economic development. In this paper, we construct a tripartite game model to explore the strategic choices of the public, merchants and the government in order to effectively respond to the panic buying behavior in the epidemic. The results demonstrate that: (1) Eight evolutionary stable strategies emerge in the panic buying events. The worst scenario can be improved by adjusting some relevant parameters. (2) The probability of the public choosing the strategy of “not involving in panic buying” depends on the potential benefits and losses of snapping up, rather than the extent of price rising. (3) The probability of merchants choosing the strategy of “not bid up price” depends on the intangible benefits. (4) The probability of the government choosing the strategy of “active supervision” depends on the supervision costs and government credibility, rather than the amount of fines. In addition, strategic suggestions to mitigate panic buying behavior are put forward from the perspective of each stakeholder.     

Strategic reference points in family firms

Family firms are classically seen as risk averse organizations, and this is evident in their generally lower R&D investments compared to non-family firms. Recent research, however, challenges this predominant view and suggests that family firms can embrace higher strategic risk when faced with threats to their family-centered goals. Still, the internal and external conditions that drive variations in the strategic risk taking behaviors of family firms are little known and understood. This article adds to this literature by developing and testing a conceptual model of strategic risk taking that incorporates behavioral theory, family business literature, and the logic of the strategic reference point theory. With recognition that the interplay between family and economic goals determines heterogeneity in strategic actions of family firms, this model suggests that family managers respond differentially to the feedback information regarding internal and external reference points, and consequently identifies key drivers of variation in the R&D investment behavior of family firms. By examining the pattern in R&D investments of 437 Spanish private manufacturing firms from 2000 to 2006, this study shows how strategic inputs, strategic outputs, and external benchmarks produce variations in strategic decisions about R&D investments in family and non-family firms. The findings offer insights into how internal and external reference points are considered in family firms’ decision making, thereby contributing a deeper understanding into the circumstances under which family goals cope or collide with the economic goals of the firm, and how this influences strategic risk decisions in family firms.     

Assessing new empirical industrial organization (NEIO) methods: The cases of five industries

The methods proposed in the new empirical industrial organization (NEIO) literature have made significant contributions to our understanding of competitive behavior. However, these methods have yet to be compared with each other for their performance in explaining and diagnosing competitive market conduct. This inter-method comparison is important because conclusions about competitive behavior based on these methods have significant strategic as well as policy implications for firms. Our objective in this paper is to examine the performance of these different NEIO methods in terms of their discriminatory power, ability to identify strategic variables, and robustness in estimation. For empirical demonstration, we use data from diverse industries such as microprocessors, personal computers, facial tissue, disposable diapers and automobiles. Our results suggest that two commonly used NEIO methods-conjectural variation and non-nested model comparison-exhibit quite good convergence with each other and are consistent with a traditional time series method. This suggests that simpler methods such as conjectural variations deserve more credit. We also find that using these methods in tandem provides valuable additional information that may not be available when using any one method alone. While the emphasis in this study is on comparing different methods of analyzing competitive interaction, the findings also reveal some substantive insights about each market studied.     

A Martingale Representation Result and an Application to Incomplete Financial Markets

We establish necessary and sufficient conditions for an H¹-martingale to be representable with respect to a collection, of local martingales. M H¹( P ) is representable if and only if M is a local martingale under all p.m.'s Q which are "uniformly equivalent" to P and which make all the elements of local martingales (Theorem 1.1). We then give necessary and sufficient conditions which are easier to verify, and only involve expectations (Theorem 1.2). We go on to apply these results to the problem of pricing claims in an incomplete financial market-establishing two conjectures of Harrison and Pliska(1981).     

Evaluating Facilitated Modelling Processes and Outcomes: An Experiment Comparing a Single and a Multimethod Approach in Group Model Building

Facilitated modelling approaches have been suggested as helpful tools to support negotiation in strategic analysis processes due to their potential to facilitate cognitive change and enhance consensus and commitment with final decisions. In the present research, we developed an experimental framework to compare what two of these approaches, that is, group model building and a multimethod approach, contribute to the process and outcomes in the negotiation of strategies. In the multimethod approach, we combined strategic options development and analysis with computer simulations of the group model building approach. We explored the differences between these two modelling approaches in facilitating cognitive change, consensus and commitment by building an experimental research design with real clients, working on their organisation’s problem. Furthermore, we compared the type and content of participants’ contributions in the strategic conversation. The lessons from the experiment conducted are twofold. On one hand, the multimethod approach encouraged more divergent contributions and produced a higher degree of cognitive change than group model building (i.e., the single approach). On the other hand, group model building encouraged more contributions about content related to causes of the problem and enhanced more commitment to the final solution than the multimethod approach. Hence, the conducted experiment brings new insights into the benefits of using multimethods and possible losses resulting from such combinations. Accordingly, we have presented opportunities for further research regarding the combination of facilitated modelling approaches.     

The Dynamics of SME Information Systems

The process by which small firms (SMEs) invest in and gain benefit from information systems (IS) is little understood. This paper analyses two alternative models of IS-based strategic change – the Focus-Dominance model (Levy et al., 2001) and stages of growth models as applied to SMEs. An analysis of the outcomes of IS strategy development undertaken for 43 SMEs maps their IS use over time. The analysis supports the Focus-Dominance model, some parts of the stages of growth model and extends the critique of the latter. Further variances are explained by the entrepreneur/owner's values and experience. One structural variable, namely, the industry sector may also explain the variances. The implications for theory and practice are discussed.     

Online Privacy Policies and Diffusion Theory Perspectives

ABSTRACT

The use of the Internet and related technologies in data sharing and new product development, which essentially serves as a foundation for the management of data flows for strategic IT, are rapidly expanding. The innovation clusters and frameworks to characterize recent e-commerce sites' privacy policies to ensure confidentiality of personal information have been under increasing academic inquiries. An application of Rogers' (1995) diffusion of innovation or technology concepts as applied to the Internet is used to develop several models of e-commerce related security and privacy concerns. One possible solution discussed is the strategic leveraging of a consortium model, providing for governmental assurances of privacy and security. Unfortunately, the current e-commerce model has no governing body to represent the consumer and e-tailer in terms of privacy and security issues so critical to the continued growth and success of the Internet.