The relationship between legitimacy,reputation, sustainability and branding for companies and their supply chains

This paper aims at filling a gap that we perceive to exist in the scientific literature as to legitimacy, reputation and sustainability and their interrelationship to corporate and supply chain branding. A series of innovative theoretical frameworks are provided interrelating companies and their value (supply) chains with legitimacy, reputation, and branding which are essential conditions to achieve sustainability and competitive advantage based on dyadic and social context consonance to the benefit of society and all stakeholders involved. An urgently required better understanding of the concepts and their interrelations is enhanced by a synthesized explanatory basis entailing an eclectic mosaic of interdisciplinary theories (institutionalist, neo-institutionalist theories, the viable system approach, isomorphism and identity) to improve corporate and supply chain performance. To better inform managerial practice the theoretical considerations are spiced with case studies among which especially the currently debated supply chain case of the European horse meat scandal is illuminated suggesting concrete managerial cross-functional implications in the food industry. The paper culminates in the call for a newly to-be-established marketing stream we call ‘Sustainable and Curative Marketing’.     

Extending the enterprise evolution contextualisation model

Enterprise engineering (EE) emerged as a new discipline to encourage comprehensive and consistent enterprise design. Since EE is multidisciplinary, various researchers study enterprises from different perspectives, which resulted in a plethora of applicable literature and terminology, but without shared meaning. Previous research specifically focused on the fragmentation of knowledge for designing and aligning the information and communication technology (ICT) subsystem of the enterprise in order to support the business organisation subsystem of the enterprise. As a solution for this fragmented landscape, a business-IT alignment model (BIAM) was developed inductively from existing business-IT alignment approaches. Since most of the existing alignment frameworks addressed the alignment between the ICT subsystem and the business organisation subsystem, BIAM also focused on the alignment between these two subsystems. Yet, the emerging EE discipline intends to address a broader scope of design, evident in the existing approaches that incorporate a broader scope of design/alignment/governance. A need was identified to address the knowledge fragmentation of the EE knowledge base by adapting BIAM to an enterprise evolution contextualisation model (EECM), to contextualise a broader set of approaches, as identified by Lapalme. The main contribution of this article is the incremental development and evaluation of EECM. We also present guiding indicators/prerequisites for applying EECM as a contextualisation tool.     

Critical success factors determining performance of cross‐border acquisition: Evidence from the African telecom market

This study investigates the factors affecting Bharti Airtel's cross‐border postacquisition performance in an African market. This study describes the relationships among various factors such as technical capability, affiliated firm's absorptive capacity, and organizational learning capabilities, which determine the successful operations of the Zain acquisition deal in South Africa. This paper adopts a qualitative approach to identify factors that influence the postacquisition performance. Seven factors are identified based on the literature. Consequently, it has become a necessity to encapsulate these factors in suitable proportions. In this study, we have developed a total interpretive structural modeling (TISM) to analyze the postacquisition performance of Bharti Airtel in South Africa. Our research has highlighted six dynamic factors (organizational learning capability, knowledge management, technology capability, technology relatedness, acquirer's absorptive capacity, and national culture difference) that affect the firm's postacquisition performance. The interpretive structural model (ISM) and total interpretive structural model for postacquisition performance are built‐up. The developed TISM will support academics and practitioners to develop their understanding of acquisition performance of parent companies in the context of telecom business in the South African market.     

Shrouding Add‐On Information: An Experimental Study*

We explore how increased competition affects firms’ obfuscation strategies in a laboratory experiment. Firms sell a base good and an add‐on product. Besides choosing the base‐good price, sellers take an action that mimics the effects of shrouding the add‐on product. Shrouding is an equilibrium but an unshrouding equilibrium coexists. In our experiment, more competition matters, in that only duopolistic markets are frequently shrouded whereas four‐firm markets are not. With repeated interaction, shrouding rates do not increase. However, the opportunities to shroud facilitate tacit collusion on the base‐good price for the duopolies: the unshrouding equilibrium serves as a credible punishment if deviations occur.     

Varying Coefficient Regression Models: A Review and New Developments

Varying coefficient regression models are known to be very useful tools for analysing the relation between a response and a group of covariates. Their structure and interpretability are similar to those for the traditional linear regression model, but they are more flexible because of the infinite dimensionality of the corresponding parameter spaces. The aims of this paper are to give an overview on the existing methodological and theoretical developments for varying coefficient models and to discuss their extensions with some new developments. The new developments enable us to use different amount of smoothing for estimating different component functions in the models. They are for a flexible form of varying coefficient models that requires smoothing across different covariates' spaces and are based on the smooth backfitting technique that is admitted as a powerful technique for fitting structural regression models and is also known to free us from the curse of dimensionality.     

Order-invariant tests for proper calibration of multivariate density forecasts

Established tests for proper calibration of multivariate density forecasts based on Rosenblatt probability integral transforms can be manipulated by changing the order of variables in the forecasting model. We derive order-invariant tests. The new tests are applicable to densities of arbitrary dimensions and can deal with parameter estimation uncertainty and dynamic misspecification. Monte Carlo simulations show that they often have superior power relative to established approaches. We use the tests to evaluate generalized autoregressive conditional heteroskedasticity-based multivariate density forecasts for a vector of stock market returns and macroeconomic forecasts from a Bayesian vector autoregression with time-varying parameters.     

New ventures in Cleantech: Opportunities,capabilities and innovation outcomes

Facing the challenge of climate change, innovations that imply environmental benefits create business opportunities for entrepreneurs. This paper analyzes innovation capabilities of startups in Cleantech and how the innovation outcomes of those startups develop over time. Based on the Mannheim Foundation Panel and applying propensity score matching, a cohort of 567 Cleantech startups is analyzed and compared with a control cohort of non‐Cleantech startups. We find that startups in Cleantech have, on average, higher technological capabilities compared with all other startups. Our econometric evidence shows that Cleantech startups are more likely to combine existing technology in a novel way. Finally, we find that Cleantech startups develop more market novelties in subsequent years when compared with their control group peers.     

A solution to log of dependent variables with negative observations

Journal of Productivity Analysis - Negative observations pose a problem in econometric models that apply log-transformation to the data. We propose a simple yet effective solution to this problem...