An Improved Security Requirement for Data Perturbation with Implications for E‐Commerce

With the rapid increase in the ability to store and analyze large amounts of data, organizations are gathering extensive data regarding their customers, vendors, and other entities. There has been a concurrent increase in the demand for preserving the privacy of confidential data that may be collected. The rapid growth of e‐commerce has also increased calls for maintaining privacy and confidentiality of data. For numerical data, data perturbation methods offer an easy yet effective solution to the dilemma of providing access to legitimate users while protecting the data from snoopers (legitimate users who perform illegitimate analysis). In this study, we define a new security requirement that achieves the objective of providing access to legitimate users without an increase in the ability of a snooper to predict confidential information. We also derive the specifications under which perturbation methods can achieve this objective. Numerical examples are provided to show that the use of the new specification achieves the objective of no additional information to the snooper. Implications of the new specification for e‐commerce are discussed.     

Confidentiality Constraints Within Mergers and Acquisitions: Gaining Insights Through a ‘Bubble’ Metaphor*

Mergers and acquisitions are extremely sensitive, both within and outside the organizations involved. Confidentiality agreements are therefore essential for allowing teams the ‘space’ to develop potential scenarios for future integration. Despite the importance of confidentiality in practice, the subject has received little coverage in the management literature. By adopting a case‐study approach, this research explores aspects of confidentiality in a four‐year post‐acquisition integration programme in a FTSE100 pharmaceutical company. The paper identifies a range of personal impacts on the signatories, as well as various dimensions of information transfer despite the agreement being in place. Through the use of a metaphor, the research suggests that a confidentiality agreement has many similarities with the properties and characteristics of a bubble. This bubble trope is used to enhance conceptual understanding of confidentiality constraints in an organizational‐change context. The paper concludes by suggesting some ‘key learnings’ in relation to using confidentiality agreements in strategic change programmes such as a merger or acquisition.     

An Enhanced Data Perturbation Approach for Small Data Sets

As modern organizations gather, analyze, and share large quantities of data, issues of privacy, and confidentiality are becoming increasingly important. Perturbation methods are used to protect confidentiality when confidential, numerical data are shared or disseminated for analysis. Unfortunately, existing perturbation methods are not suitable for protecting small data sets. With small data sets, existing perturbation methods result in reduced protection against disclosure risk due to sampling error. Sampling error may also produce different results from the analysis of perturbed data compared to the original data, reducing data utility. In this study, we develop an enhancement of an existing perturbation technique, General Additive Data Perturbation, that can be used to effectively mask both large and small data sets. The proposed enhancement minimizes the risk of disclosure while ensuring that the results of commonly performed statistical analyses are identical and equal for both the original and the perturbed data.     

Incorporating social networks into leadership development: A conceptual model and evaluation of research and practice

Multilevel and relational views of leadership are expanding the focus of leadership development beyond individuals' knowledge, skills, and abilities to include the networked patterns of social relationships linking members of dyads and larger collectives. In this review, we present a conceptual model explaining how three distinct approaches for network-enhancing leadership development can improve the leadership capacity of individuals and collectives. We then present a review of the leadership development literature and the results of a survey of 282 practitioners to assess the extent to which these approaches have been examined in research and implemented in practice. Our review revealed that leadership research and leadership development practice are outpacing leadership development research in terms of incorporating networks. We aim to spur future research by clarifying the targets, objectives, and underlying mechanisms of each network enhancing leadership development approach in our conceptual model. Further, we identify additional literature, not traditionally considered within the realm of leadership development that may help advance empirical examinations of these approaches.     

Modeling of interventions for reducing external Enterobacteriaceae contamination of broiler carcasses during processing

This article presents a mathematical model for the Enterobacteriaceae count on the surface of broiler chicken during slaughter and how it may be affected by different processing technologies. The model is based on a model originally developed for Campylobacter and has been adapted for Enterobacteriaceae using a Bayesian updating approach and hitherto unpublished data gathered from German abattoirs. The slaughter process in the model consists of five stages: input, scalding, defeathering, evisceration, washing, and chilling. The impact of various processing technologies along the broiler processing line on the Enterobacteriaceae count on the carcasses’ surface has been determined from literature data. The model is implemented in the software R and equipped with a graphical user interface which allows interactively to choose among different processing technologies for each stage along the processing line. Based on the choice of processing technologies the model estimates the Enterobacteriaceae count on the surface of each broiler chicken at each stage of processing. This result is then compared to a so-called baseline model which simulates a processing line with a fixed set of processing technologies. The model calculations showed how even very effective removal of bacteria on the exterior of the carcass in a previous step will be undone by the cross-contamination with leaked feces, if feces contain high concentrations of bacteria.     

Crafting business models for conflicting goals: Lessons from creative service firms

The business model construct has become attractive to both managers and academics. It reflects how the most important organization's strategic and tactical choices regarding the allocation of resources interact in order to create and capture value. Yet with the growing entrepreneurial complexity, managers often end up pursuing conflicting and even paradoxical strategic goals, thus rendering the business modelling processes more complex, too. Well-known examples are profit versus social value, stakeholder versus company interests, exploration versus exploitation and environmental sustainability versus economic returns. The academic business model literature so far has provided limited insights on how to implement business models beyond a single goal and focused mainly on the initial strategic choice of a business model, ignoring that such salient tensions are often persistent and resurface within the business practice. In this study we leverage paradox theory to investigate how managers of creative firms make tactical choices to accommodate (not solve) salient tensions within their business models, focusing on the domains like services provided, choice of clients, networking and resourcing practices, revenue models and new venture creation. Based on qualitative case study research, we found four integrating and three differentiating decision-making tactics that managers deploy to create both economic and creative value through their business models. Adding to the business model theory, we show how business models are crafted in managerial practices by making tactical decisions to solve conflicts and paradoxes. The results equally enrich the paradox literature by providing for tactical-level approaches toward working through the paradox.     

Measuring agri-food supply chain performance and risk through a new analytical framework: a case study of New Zealand dairy

Abstract

Many researchers and practitioners have long recognized the significance of measuring performance. Although general guidelines for measuring business performance are widely available, no appropriate measurement frameworks have been developed for measuring agri-food supply chain performance. Particularly, food quality and risk-related indicators have not been well integrated into existing performance measurement systems. Our research, therefore, addresses this knowledge gap by first providing an in-depth review of extant performance measurement systems and frameworks. It then develops an analytical framework by extending the Supply Chain Operations Reference (SCOR) model which has been extensively implemented across non-food industries. The analytical framework is further validated by utilizing a case study of 50 farmers and 10 dairy companies, operating in the New Zealand dairy industry.

Our pilot testing and subsequent findings show that the individual metrics interlocked with the analytical framework are in-line with the key industrial practices adapted by the New Zealand dairy industry. In addition, the framework is flexible and scalable to evaluate and benchmark other agri-food supply chains – ranging from fresh products such as fruits and vegetables to processed foods such as canned fruits. The findings further show that the detailed information required for measuring the level-3 SCOR metrics is not easily available in the industry, as researchers need to access specific company records that may be confidential. Consequently, this study provides how agri-food supply chain managers can employ our new analytical framework in-conjunction with the SCOR model for a deeper understanding of the complicated performance measurement indicators applied in their agri-food production systems and relevant supply chains.     

Bubbles and Crashes

We present a model in which an asset bubble can persist despite the presence of rational arbitrageurs. The resilience of the bubble stems from the inability of arbitrageurs to temporarily coordinate their selling strategies. This synchronization problem together with the individual incentive to time the market results in the persistence of bubbles over a substantial period. Since the derived trading equilibrium is unique, our model rationalizes the existence of bubbles in a strong sense. The model also provides a natural setting in which news events, by enabling synchronization, can have a disproportionate impact relative to their intrinsic informational content.     

Simple Finite Horizon Bubbles Robust to Higher Order Knowledge

An asymmetric information model of a finite horizon “nth order” rational asset price bubble is presented, where (all agents know that)ⁿ the asset is worthless. Also, the model has only two agents, so the first order version of the bubble is simpler than other first order bubbles in the literature.     

A general space-time model for combinatorial optimization problems (and not only)

We consider the problem of defining a strategy consisting of a set of facilities taking into account also the location where they have to be assigned and the time in which they have to be activated. The facilities are evaluated with respect to a set of criteria. The plan has to be devised respecting some constraints related to different aspects of the problem such as precedence restrictions due to the nature of the facilities. Among the constraints, there are some related to the available budget. We consider also the uncertainty related to the performances of the facilities with respect to considered criteria and plurality of stakeholders participating to the decision. The considered problem can be seen as the combination of some prototypical operations research problems: knapsack problem, location problem and project scheduling. Indeed, the basic brick of our model is a variable x_ilt which takes value 1 if facility i is activated in location l at time t, and 0 otherwise. Due to the conjoint consideration of a location and a time in the decision variables, what we propose can be seen as a general space-time model for operations research problems. We discuss how such a model permits to handle complex problems using several methodologies including multiple attribute value theory and multiobjective optimization. With respect to the latter point, without any loss of the generality, we consider the compromise programming and an interactive methodology based on the Dominance-based Rough Set Approach. We illustrate the application of our model with a simple didactic example.     

Mixed contracts for the newsvendor problem with real options and discrete demand

In this paper we consider the newsvendor model with real options under discrete demand. We consider a mixed contract where the retailer can order a combination of q units subject to the conditions in a classical newsvendor contract and Q real options on the same items. We provide a closed form solution to this mixed contract when the demand is discrete and study some of its properties. In particular we demonstrate that a mixed contract may be superior to a real option contract when a manufacturer has a bound on how much variance she is willing to accept.     

The relative value of a management information system,a simulation study

A relative value of a management information system (MIS) is defined in this paper by a ratio $\text{u}{}_1\text{u}{}_0$, where u₀ is a value of a utility function of an enterprise whose management information system is perfect, and u₁ is its value when it is not perfect and may produce inaccurate or out-of-date data among correct information. Our simulation model contains beuristics which describe the operational and strategic information system of an enterprise. The environment of the enterprise may be stable or dynamic. A mathematical formula, based on simulations, is developed. This formula describes how the relative value of an MIS depends on such factors as the accuracy of an operational information system, delays in information flow, the quality of a strategic information system, a reinvestment ratio used in the enterprise, and a number of investment periods. This formula has been found suitable in an enterprise with a strategically stable environment, but not with a turbulent environment.     

Follower behavior renders leader behavior endogenous: The simultaneity problem,estimation challenges,and solutions

Traditionally, leadership research has focused on unidirectional questions in which leader attributes are considered to determine follower outcomes. However, many phenomena between leaders (x) and followers (y) involve a simultaneous influence process in which x affects y, and y also affects x (i.e., simultaneity). Unfortunately, this simultaneity bias creates endogeneity and is often not properly addressed in the extant leadership literature. In three studies, we demonstrate the challenges of simultaneity bias and present two methodological solutions that can help to correct problems of simultaneity bias. We focus on simultaneity that occurs between follower resistance and leader control. We mathematically demonstrate the simultaneity bias using a simulated dataset and show how this bias can be statistically solved using an instrumental variable estimation approach. Furthermore, we present how the simultaneity bias can be resolved using an experimental design. We discuss how our approach advances theory and methods for leadership research.     

The Effects of Agglomeration and National Property Rights on Digital Confidentiality Performance

In recent years, instances of organizations failing to maintain digital confidentiality performance have greatly increased in frequency and monetary damage. While the global sourcing of activities in the development of digital assets is widespread, very little is known about how location‐related factors may affect confidentiality outcomes. Addressing this, we empirically investigate two factors with rich theoretical bases and logical linkages to confidentiality: industrial agglomeration and national property rights protections. We conduct a large‐scale, empirical study at the product level of analysis, and treat the confidentiality of a digital product as a performance outcome that is affected by the locations of the two key organizational entities involved in the product's development. We leverage modern, web‐crawling methods to harvest secondary data from a major, illicit distribution channel for these products and combine these data with other secondary data involving legitimate commerce to derive a secondary measure of confidentiality performance. We find robust results, and demonstrate practical significance of our findings through scenario analyses based on actual data from our sample.     

Employee attitudes to work-based counselling services

Abstract

Work-based counselling services have increasingly been introduced in organizational settings in the 1980s and 1990s. In this paper, a study is reported of the attitudes of 213 employees of a UK Health Authority towards an existing counselling service. Questionnaires sought information about attitudes to counselling, confidentiality, attitudes to those seeking counselling and general health. The results suggested that attitudes to work-based counselling services are predicted by employees' perceptions of those seeking counselling as trustworthy and their beliefs about the confidentiality of the service. The practical implications of these results are examined.     

Corporate social responsibility: the organizational view

Designing strategies for corporate social responsibility (CSR)-practice nowadays has become essential for organizations. Notwithstanding, how organizations appear internally in a socially responsible context toward their employees has been insufficiently investigated. This study aims at ascertaining how Internal CSR can be conceptualized as well as how it affects employees’ commitment. To do so, the manifestations of Internal CSR are discussed based on social identity theory and further literature, while the developed research model is checked for suitability through a survey generating 2081 employee responses from an international pharmaceutical company. As one result, it can be stated that the factors proposed to constitute Internal CSR are confirmed. Further, the findings entail the following conclusions: Internal CSR has a notable influence on employees’ Affective Organizational Commitment whilst relatively moderate impacting Normative Organizational Commitment. Additionally, Affective Organizational Commitment adopts a mediating function regarding Normative Organizational Commitment.     

Examining the role of Donald Trump and his supporters in the 2021 assault on the U.S. Capitol: A dual-agency model of identity leadership and engaged followership

This article develops a dual-agency model of leadership which treats collective phenomena as a co-production involving both leaders and followers who identify with the same social group. The model integrates work on identity leadership and engaged followership derived from the social identity approach in social psychology. In contrast to binary models which view either leaders or followers as having agency, this work argues that leaders gain influence by defining the parameters of action in ways that frame the agency of their followers but leave space for creativity in how collective goals are accomplished. Followers in turn, exhibit their loyalty and attachment to the leader by striving to be effective in advancing these goals, thereby empowering and giving agency to the leader. We illustrate the model primarily through the events of 6th January 2021 when Donald Trump’s exhortations to his supporters that they should ‘fight’ to ‘stop the steal’ of the 2020 election was followed by an attack on the United States’ Capitol. We argue that it is Trump’s willing participation in this mutual process of identity enactment, rather than any instructions contained in his speech, that should be the basis for assessing his influence on, and responsibility for, the assault.     

Variability and Uncertainty Analysis of the Cross‐Contamination Ratios of Salmonella During Pork Cutting

The transfer ratio of bacteria from one surface to another is often estimated from laboratory experiments and quantified by dividing the expected number of bacteria on the recipient surface by the expected number of bacteria on the donor surface. Yet, the expected number of bacteria on each surface is uncertain due to the limited number of colonies that are counted and/or samples that can be analyzed. The expected transfer ratio is, therefore, also uncertain and its estimate may exceed 1 if real transfer is close to 100%. In addition, the transferred fractions vary over experiments but it is unclear, using this approach, how to combine uncertainty and variability into one estimate for the transfer ratio. A Bayesian network model was proposed that allows the combination of uncertainty within one experiment and variability over multiple experiments and prevents inappropriate values for the transfer ratio. Model functionality was shown using data from a laboratory experiment in which the transfer of Salmonella was determined from contaminated pork meat to a butcher's knife, and vice versa. Recovery efficiency of bacteria from both surfaces was also determined and accounted for in the analysis. Transfer ratio probability distributions showed a large variability, with a mean value of 0.19 for the transfer of Salmonella from pork meat to the knife and 0.58 for the transfer of Salmonella from the knife to pork meat. The proposed Bayesian model can be used for analyzing data from similar study designs in which uncertainty should be combined with variability.     

Managing Internal R&D Networks in Global Firms: What Sort of Knowledge is Involved?

How should a global firm manage its network of R&D centres in an effective manner? Some have developed an Integrated Network model in which the R&D centres around the world are tightly integrated into a coherent whole. Others have adopted a Loosely-Coupled Network model in which individual “centres of excellence” are given considerable autonomy. In this paper we argue that the way individual R&D units are structured, and the way the entire network is managed, should be based not on administrative heritage, environmental turbulence or management style, but on the basis of the underlying characteristics of the firm’s knowledge assets. In particular we focus on the observability and mobility of the firm’s knowledge assets, the impact these factors have on the way individual R&D centres are structured, and how they relate to one another in the international network. The argument is supported using examples and data from Swedish firms including ABB, Alfa Laval and Ericsson.     

Improving spare parts inventory control at a repair shop

We study spare parts inventory control for an aircraft component repair shop. Inspection of a defective component reveals which spare parts are needed to repair it, and in what quantity. Spare part shortages delay repairs, while aircraft operators demand short component repair times. Current spare parts inventory optimization methods cannot guarantee the performance on the component level, which is desired by the operators. To address this shortfall, our model incorporates operator requirements as time-window fill rate requirements for the repair turnaround times for each component type. In alignment with typical repair shop policies, spare parts are allocated on a first come first served basis to repairs, and their inventory is controlled using (s, S) policies. Our solution approach applies column generation in an integer programming formulation. A novel method is developed to solve the related pricing problem. Paired with efficient rounding procedures, the approach solves real-life instances of the problem, consisting of thousands of spare parts and components, in minutes.A case study at a repair shop reveals how data may be obtained in order to implement the approach as an automated method for decision support. We show that the implementation ensures that inventory decisions are aligned with performance targets.