Search results

This study explores the nature and role of CEO discourse in mergers and acquisitions (M&A), and especially during the highly complex post-merger integration process. Abstraction from two extensive empirical data sources suggests that executive discourse in M&A can be seen as fitting a taxonomy involving four categories: dubbed the cartel, aesthetic, videogame and holistic communicator. It is furthermore purported that executive sense-making through discourse may need to be monitored around an ideal and permanently oscillating distance between the executive promise and the many different realities that stakeholders experience in the post-merger process: too little distance prevents change from happening, too much distance erodes the belief in the promised possibilities. This distance, named the promise–realities gap, is different for each (type of) stakeholder, as stakeholders perceive both the discoursed promise as also their everyday corporate realities in different manners. This individual perception of discourse and of the multitude of perceived realities and the volatility of their influencing variables exacerbate the successful management of the promise–realities gap.

Performance evaluation is a topic that has been researched and practiced extensively in business organizations but has received scant attention in higher education institutions. A review of literature revealed that context, input, process, product (CIPP) model is an appropriate performance evaluation model for higher education institutions. However, little guidance exists for choosing appropriate metrics and benchmarks in implementing the CIPP model. The purpose of this paper is to develop a framework using CIPP model for performance evaluation of higher education institutions.

To achieve the purpose of the study, a review of literature was conducted to identify an appropriate evaluation model. Then metrics and benchmarks framework were formed based on practical approaches used in a large university in the USA.

Nine perspectives in performance evaluation using the CIPP model and their application in higher education institutions were developed and discussed. The discussion provides examples, relative prevalence including frequency of usage, advantages and limitations of each of the nine perspectives of performance evaluation in higher education institutions. An actual application of the suggested CIPP model in the USA largest university, by student enrollment, was provided. Implications for institutional assessment and continuous improvement for higher education institutions were made.

The study provides a practical framework, model and guidelines that can be used by higher education institutions to evaluate and enhance their performances and better prepare students to effectively work in society.

The purpose of this paper is to explore the implications of adopting a critical realist position for the study of performance measurement and management (PMM) systems.

This paper discusses recent challenges to knowledge creation in PMM, arguing that overcoming these will require revisiting often implicit philosophical assumptions related to how the world is and how we learn about it. A critical realist perspective is explored and illustrated with the case of a software company attempting to empower and motivate its team.

Critical realism provides a means of building interdisciplinary knowledge in PMM. In addition to a generative view of causality, critical realism could augment a systems view of PMM by adopting a stratified view of reality and through its applied approach to knowledge building. The case illustrates the RRREIC approach and highlights the interplay of mechanisms of different scales and how this requires interdisciplinarity.

Approaching the study of PMM with critical realism requires going beyond a particular tool or practice to understand the theory behind it. Such an approach can facilitate a layered, nuanced analysis of the issues facing organizations in a changing context.

This paper adds to discussion of philosophical topics in management and PMM and could help resolve ongoing challenges to knowledge building in the field, especially around barriers to conducting interdisciplinary research. In combination with rigorous methods, a strong philosophical base can facilitate relevant, lasting theories that can respond to a changing organizational context.

All food safety management standards require effective control measures of food safety hazards in order to ensure that food is safe at the time of human consumption. Furthermore, ISO 22000:2005 requires a logical approach to be carried out for the selection and categorization of the control measures according to the level of effect on identified food safety hazards. The purpose of this paper is to describe the COntrol MEasures CATegorization (COMECAT) method for the categorization of control measures in food safety management systems (FSMS) in order to assist organizations to prioritize and deploy their efforts and limited resources mainly to control significant hazards.

A thorough clarification of the characteristics of the different control measures used in FSMS has been achieved based on the definitions and the descriptions given by the different food safety standards such as the ISO 22000, the IFS and the BRC standards. The basic approaches for the determination of control measures found in literature and web pages have been examined and the proposed methodology has been implemented in feta cheese production in order to evaluate its applicability.

A decision tree model has been proposed as the most suitable approach for the categorization of control measures in FSMS. The implementation of the proposed COMECAT method in feta cheese production revealed its applicability. The method was able to identify the different risk level of food hazards and prioritize and deploy the organization’s efforts and limited resources for their management accordingly.

In the literature, there is a lack of justified methodologies for the categorization of control measures in FSMS. Most of the approaches concern attempts of private companies operating in the food industry or business consultancies and which can be found in their web pages. This paper describes a well-justified model for the categorization of control measures which is easy to implement and which results in more robust decisions.

The purpose of this study is to focus on the policy of corporate social responsibility (CSR) launched in the chemical industry in the 1980s and known as “Responsible Care” (RC). The debate surrounding this issue prompts us to question the ever‐changing nature of this policy and the way to measure the performance achieved.

The findings are drawn from analysis of a double set of data including a longitudinal survey and a current case study. Blending these two data sets allows a better understanding of the ongoing building process of “RC” and, more broadly, of CSR.

This paper asserts that, contrary to the common wisdom developed in research, companies do not simply react to stakeholder pressure. Companies autonomously develop ways to protect their environment and so contribute to changing society's expectations. Thus, performance cannot be read without a dynamic perspective in mind.

The authors' findings lead them to reconsider the assessment of companies' sustainable performances by taking into account the fabricating process of sustainable activities. The main limitation of this research stems from the single unit of analysis considered. Broader studies will be necessary to enrich our understanding of corporate policies.

The paper stands apart from the traditional view of organizations as cynical actors and attempts to provide a more complex picture of the behaviours observed.

This study examines the role of crowd wisdom in misinformation correction. Going beyond fact-checking, we investigate the mechanisms underlying laypeople’s participation in misinformation correction. Drawing upon the Norm Activation Model (NAM), this study conceptualizes misinformation correction as a prosocial behavior and examines the impact of various media and social psychological factors on laypeople’s motivations to engage misinformation correction behavior.

Through a national survey of 1,022 respondents, we explore the norm activation process triggered by the perceived prevalence of online misinformation, which directly and indirectly impacts online misinformation correction intentions via awareness, norms, and efficacy. This mechanism was tested using structural equation modeling.

This study found that perceived prevalence of misinformation, self-efficacy, and outcome efficacy play multilayered roles in shaping misinformation correction intentions. The effects were mediated by the activation of personal norms, which showed the strongest direct relationship with correction intentions. However, these factors also demonstrated direct associations with correction intentions, indicating multiple paths in misinformation correction.

Differing from mainstream fact-checking approaches, this study provides a more comprehensive examination of the mechanisms underlying laypeople’s willingness to engage in social media misinformation correction behaviors. In addition, this study also extends NAM by incorporating media environment (perceived prevalence of online misinformation) into the model, identifying more paths affecting misinformation correction behaviors.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0437

Purpose: The main purpose of the study is to understand the factors that facilitate correction behavior among individuals. In this study the authors examine the impact of self-perceived media literacy (SPML) and reflection on participants’ correction behavior.

Methods: Data for the study were collected from Amazon's MTurk using an online survey. Data were collected after a certificate of exemption was received by the Institutional Review Board in a research university in the United States (US) Qualtrics software was used to collect data. The total number of participants was 797.

Findings: The findings show that although both SPML and reflection are positively associated with rumor refutation, higher SPML alone is not enough. Reflective judgment is critical for individuals to take part in this behavior online, such that individuals with higher reflective judgment indicated that they refute rumors online, irrespective of their SPML score.

Originality: The authors tested the relationship of multiple variables with participants correction behavior. Although research shows the importance of social correction, there is not much knowledge about what facilitates actual misinformation correction.

This article sets out to examine the common organizational problem of inadequate tracking and follow‐through of cross‐functional corrective actions and strategic objectives. Various solutions were tested to develop a “best practice” for improving the effectiveness and accountability of implementing action plans.

Program audits were conducted on the tracking and effectiveness of strategic objectives and corrective action plans at 24 aerospace‐related companies (e.g. Northrop, Allied Signal) in the USA.

Generally, strategic objectives and correction actions are performed adequately and on‐time within an organization's function (e.g. engineering). The adequacy of cross‐functional actions, however, was a completely different story. Typically, these actions were delayed past the “need by dates” and often failed to satisfy the internal customer's need. Several solutions were examined and “the dynamic stringing” method proved to be the most effective.

Future studies need to focus on additional methods to insure accountability of cross‐functional requirements to include incentives.

This study presents the basis for a “best practice” that could help solve inefficiencies and delays in completing cross‐functional actions. The core concept of “paper and string” can easily be upgraded to computerized project management systems. The key, however, is not to lose the power of “visibility.”

This is the only study that has examined the chronic problem or “dirty little” secret of poor cross‐functional support in numerous organizations. The value is to managers that need to insure the accomplishment of strategic objectives and corrective actions.

The paper aims to discuss error detection and correction in Kashmiri carpet weaving (KCW), mediated by cryptographic code, Talim which is held to guarantee accurate information transference from designing to weaving, even after hundred years. Yet, carpets often show errors on completion.

Human factors analysis revealed error emergence, detection and correction in this practice whose task domains are distributed over large geographies (from in-premises to several kilometers) and timescales (from days to decades). Using prospective observation method, production process of two research carpets from their design, coding and weaving was observed while noting the errors made, identified and corrected by actors in each phase.

The errors were found to emerge, identified and corrected during different phases of designing, coding and weaving while giving rise to fresh errors in each phase, due to actors’ normal work routines.

In view of this, usual branding of “weaver-error” behind flawed carpet turns out to be misplaced value judgment passed in hindsight.

The purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines.

Event trees are adopted to model errors in the picking-handling-delivery-utilization of materials containers from the warehouse to assembly stations. Error probabilities and quality costs functions are developed to compare alternative feeding policies including kitting, line stocking and just-in-time delivery. A numerical case study is included.

This paper confirms with quantitative evidence the economic relevance of logistic errors (LEs) in parts feeding processes, a problem neglected in the existing literature. It also points out the most frequent or relevant error types and identifies specific corrective measures.

While the model is general purpose, conclusions are specific to each applicative case and are not generalizable, and some modifications may be required to adapt it to specific industrial cases. When no experimental data are available, human error analysis should be used to estimate event probabilities based on underlying modes and causes of human error.

Production managers are given a quantitative decision tool to assess errors probability and errors correction costs in assembly lines parts feeding systems. This allows better comparing of alternative parts feeding policies and identifying corrective measures.

This is the first paper to develop quantitative models for estimating LEs and related quality cost, allowing a comparison between alternative parts feeding policies.