Consumer Responses to the Food Industry’s Proactive and Passive Environmental CSR,Factoring in Price as CSR Tradeoff

This study explores social enterprises’ strategies for addressing mission drift. Relying on an inductive comparative case study of two Italian social enterprises, we show how stakeholder engagement combined with social accounting can successfully support a social venture to re-balance its positioning between wealth generation and social value creation. Indeed, stakeholder engagement helps the internal actors of a social enterprise to rationalize and embody pro-social values previously abandoned, while social accounting reinforces this embodiment process by showing the reintroduced social commitment of the social enterprise to external audiences. Conversely, strategies focused only on social accounting and without significant engagement of external stakeholders prove to be unsuccessful in counterbalancing mission drift because they fail to activate the necessary process of internal re-introduction and operationalization of pro-social values and objectives.     

The role of brand personality,self-congruity,and sensory experience in elucidating sky lounge users’ behavior

This study attempted to develop an integrated model linking brand personality, self-image congruity, hedonic and utilitarian values, and behavioral intentions in the sky lounge context. Our results indicated that brand personality was significantly related to self-image congruity, which in turn influenced hedonic and utilitarian values. While hedonic value significantly affected intentions to revisit and recommend, utilitarian value significantly influenced intention to recommend. Moreover, self-image congruity and values played a significant mediating role. Furthermore, the links from hedonic value to intentions to revisit and recommend, and from utilitarian value to intention to revisit were significantly moderated by sensory experience.     

Patterns of technology life cycles: stochastic analysis based on patent citations

Patent analysis has been considered as an effective means of estimating phases of a technology life cycle. However, previous studies have not considered the dynamic and idiosyncratic aspects of a technology’s progression since they were based on deterministic methods, mainly fitting s- or double s-shaped curves to patent application counts. Moreover, previous methods cannot be executed at the individual patent level. We propose a stochastic technology life cycle analysis to trace the phases of a technology’s progression based on patent citations and identify the patterns of technology life cycles at the individual patent level. At the heart of the proposed approach are a hidden Markov model to estimate the probability of a system being at a certain hidden state from observation and cluster analysis to group a set of objects according to their similarities. A case study of patents about laser technology in lithography is presented.     

User participation and management information system use: A path analysis

This article proposes and empirically tests a causal model of user participation and management information system use. Based on a review of available literature, three variables including user understanding, system quality and user acceptance are identified as intervening in the relationship between user participation and system use. Causal orders among these variables are assumed and a causal model is constructed for empirical testing. Task complexity is introduced as a contingent variable affecting the structure of these causal relationships. The data are collected from 134 users of 77 different information systems in 32 Korean business firms. The results of data analysis support the causal model in general, but suggest that causal relationships among the variables are different according to task complexity. Two separate models of user participation and management information system use, based on the empirical results, are presented for further research, one for more complex and the other for less complex systems.     

The Environmentally Friendly Programs in Hotels and Customers' Intention to Stay: An Online Survey Approach

This study surveyed customer perceptions about the environmentally friendly programs (i.e., green programs) in hotels and analyzed the degree to which such programs influenced customers' hotel selection. Data were collected from online travel communities by conducting Web-based online surveys. A total of members from 63 travel-related online communities participated in the survey. Multiple regression analysis results showed that the significant factors that affected client hotel selection were: Solid waste and water programs in guestrooms, energy programs, solid waste and water programs in housekeeping, and biodiversity programs. However, water program by customers' option did not influence customer decisions to stay at environmentally friendly hotels. Results also showed differences in customer awareness and demand for environmentally friendly hotels based on gender, income, and age.     

Achieving relational outcomes in casual dining restaurants through consumer commitment

The purpose of the study is to identify how we can achieve positive word-of-mouth (WOM) and share of purchases through consumer commitment in casual dining restaurants. This study proposes the theory of organizational commitment and the framework of the relationship development process as the theoretical foundation to identify the antecedents of consumer commitment (i.e. identification, switching costs, and satisfaction), and tests the role of consumer commitment between its antecedents and relational outcomes (i.e. share of purchases and positive WOM). The results of the study support that commitment plays a partial mediating role in the relationship between its antecedents and share of purchases. In addition, commitment exerts a full mediating role on the effects of identification and switching costs on positive WOM intentions, while it plays a partial mediating role between satisfaction and positive WOM intentions. Managerial implications are discussed to maximize delivering relational outcomes based on consumer commitment and its antecedents.     

Artificial neural networks with feature transformation based on domain knowledge for the prediction of stock index futures

A feature transformation method based on domain knowledge for arti?cial neural networks (ANNs) is proposed. The method of feature transformation based on domain knowledge converts continuous values into discrete values in accordance with the knowledge of experts in speci?c application domains. This approach effectively ?lters data, trains the classi?er, and extracts the rules from the classi?er. In addition, it reduces the dimensionality of the feature space, which not only decreases the cost and time in the operation but also enhances the generalizability of the classi?er. The experimental results of the proposed approach will be compared and tested statistically with the results of the linear transformation method. The results show that the method of feature transformation based on domain knowledge outperforms the linear transformation in modelling of ANNs. Copyright © 2004 John Wiley & Sons, Ltd.     

Dividend Stickiness,Debt Covenants,and Earnings Management

Consistent with the notion that dividends are very sticky, Daniel, Denis, and Naveen ( 2008 ) report evidence that firms manage earnings upward when pre‐managed earnings are expected to fall short of dividend payments. However, we find that this evidence is not robust when controlling for firms' tendency to manage earnings upward to avoid reporting earnings declines; only firms with high leverage exhibit a statistically weak tendency to manage earnings to close deficits of pre‐managed earnings relative to dividends. We further report that the decision to cut dividends depends on whether reported earnings fall short of past dividends, but not on earnings management that eliminates a shortfall in pre‐managed earnings relative to dividend payments. Overall, our evidence suggests that firms that face dividend constraints are more likely to cut dividends than to manage earnings to avoid dividend cuts.     

Comparative advantage and unemployment

Worker heterogeneity in productivity and labor supply is introduced into a matching model. Workers who earn high wages and work high-hours are identified as those with strong market comparative advantage—high rents from being employed. The model is calibrated to match separation, job finding, and employment in the SIPP data. The model predicts a big drop in employment for workers with weak comparative advantage during recessions. But the data show that workers with strong comparative advantage also display sizable employment fluctuations, implying that aggregate employment fluctuations are not explained by the responses of workers with small rents to employment.