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Corporate responsibility perceptions from stakeholders are becoming more difficult to manage. This is in part because of large amount of social media being projected to stakeholders on a daily basis. In light of this, the purpose of this paper is to examine the relationship between corporate responsibility framing from the social media perspective firm’s performance as defined by abnormal-return (defined as the difference between a single stock or portfolios return and the expected return) and idiosyncratic-risk (defined as the risk of a particular investment because of firm-specific characteristics).

Hypotheses are developed through agenda-setting theory and stakeholder and shareholder viewpoints. The research model is tested using sentiment analysis from a collection of social media from several industries.

The results provide support that three corporate responsibility social media categories (economic, social and environmental-framing) will have different impacts (delayed, immediate) on abnormal-return and idiosyncratic-risk. This study finds differences between immediate (one-day lag) and delayed (three-day lag) associations on abnormal-return and idiosyncratic-risk.

This study also suggests differences between the amount and sentiment of corporate responsibility social media framing on abnormal-return and idiosyncratic-risk. Finally, results identify interaction effects between different corporate responsibility social media categories.

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/01443579410056065. When citing the article, please cite: James J. Hoffman, Marc J. Schniederjans, (1994), “A Two-stage Model for Structuring Global Facility Site Selection Decisions”, International Journal of Operations & Production Management, Vol. 14 Iss 4 pp. 79 - 96.

Production/operations managers want to increase the efficiency and effectiveness of their subordinates. If an ineffective subordinate cannot be terminated the operations manager must devise a means of coping with this individual. A mail questionnaire survey of manufacturing firms listed in the 1984 Standard and Poor's Register of Corporations, Directors and Executives and a parallel telephone questionnaire survey were administered to production/operations managers in the USA. One hundred and eighty‐four usable returns, representing 82 manufacturing organisations, were received. Results show that coping strategies used by production/operations managers vary as a function of the superior's age, level of management and years of experience. Coping strategies change over time. Recently passive strategies have been used to a greater extent. Previously more active strategies were used. Active strategies for dealing with ineffective subordinates are now gaining favour again.

The purpose of this paper is to compare implementation of short‐run (i.e., small lot‐size) statistical process control (SPC) techniques in just‐in‐time (JIT) manufacturing environments. Using U.S. and Japanese questionnaires, this research focuses on the use of several manufacturing elements such as setup time, stability of process and quality improvement. Barriers to the implementation of short‐run SPC techniques are also examined. Results show significant difference in the way some short‐run SPC techniques are utilized by JIT and non‐JIT manufacturers.

Presents a linear goal programming (LGP) model, which can be used to derive an optimal daily production schedule for JIT production systems. Also provides an explanation of how a detailed post‐optimal LGP analysis can enable a decision maker to examine the effects of production scheduling in a JIT “mixed‐model” production environment. To illustrate the informational efficacy of the proposed JIT‐based LGP model, presents an illustrative example.

Recent models comparing inventory costs under just‐in‐time (JIT) purchasing plans and economic order quantity (EOQ) purchasing plans have tended to favor EOQ purchasing in situations where annual demand of inventory is moderately large. Contends that these cost models are lacking dynamic cost components inherent in virtually all JIT purchasing plans. Presents a series of inventory purchasing cost models that extend prior methodology by Fazel by including relevant physical distribution cost savings. Additional comparative models are presented to further demonstrate how other relevant costs factors can be included in a comparative EOQ/JIT model. A cost comparison with an existing problem from the literature is used to illustrate the informational efficacy of new models.

One strategy that has been used extensively to cut operation costs is downsizing, a planned reduction in a firm’s work force. Downsizing must be based on a thorough analysis of the firm’s prioritized opportunities and their limited economic resources to achieve them. Some operations research techniques have appeared in the literature as practical aids in downsizing methodology. The purpose and significance of the research in this paper is to: provide the first demonstration of how a prioritized multi‐objective programming‐oriented methodology (i.e. goal programming) can be used for planning the downsizing of production/operations resources; and demonstrate a new methodological approach that can be used to determine previously hidden goals in a manufacturing linear programming model of the downsizing problem. Based on a problem reported in the literature, this paper will illustrate how an optimal allocation of production resources can be achieved while providing useful information in which to ensure other prioritized goals and their economic tradeoffs are considered in the downsizing analysis.

Many of the financial instruments used in classic investment analysis do not apply to typical information technology investment decision making because of the multi‐criteria and multi‐objective nature of the problem. This is particularly true when integrating strategic, tactical, and operations planning objectives in the decision. One approach for making IT investment decisions is a multi‐objective goal programming (GP) model proposed by Talluri in 2000. The purpose of our paper is twofold: to demonstrate how a simple ranking/scoring method can be used in place of the more involved Talluri GP modeling approach if only a solution is required; and, in decision situations where solution justification is desired, to explain how GP extension methodologies can be incorporated into the analysis to generate information to determine a solution’s reliability and identify economic tradeoffs that can be used to improve an existing solution.

The purpose of this paper is to compare the implementation of short‐run (i.e., small lot‐size) statistical process control (SPC) techniques for manufacturing between the U.S. and Japan. Using U.S. and Japanese questionnaires, this research focuses on the use of several manufacturing management elements such as setup time, stability of process, and quality improvement. These elements are compared in terms of their respective countries’ short‐run SPC techniques implementation. Barriers to the implementation of short‐run SPC techniques are also examined. In addition, this research identifies current process control techniques used to support short‐run SPC in both countries. Results show how the significantly different short‐run SPC techniques are utilized in the U.S. and Japan.

An examination of changing an inventory policy of a major manufacturing organisation and its impact on the cost structure of the organisation is presented. A classic cost confrontation between set‐up costs and inventory costs are examined in the study. The results reveal that the unique nature of the manufacturing organisation favours short‐run production scheduling over a proposed long‐run production scheduling policy. This article also presents the application of a decision support system (DSS) to aid in production scheduling. The applications reveals that improved scheduling and a reduction in scheduling time and effort can be achieved by using the DSS over the manufacturing organisations′ manual systems.