Social media affordances in entry‐level employees’ socialization: employee agency in the management of their professional impressions and vulnerability during early stages of socialization

This study examined how entry‐level employees interacted with social media during three stages of organizational socialization. They navigated between four different media affordances (persistence, editability, visibility, and association) while experiencing them as both enabling and constraining in different socialization stages. Qualitative interview data analysis revealed during anticipatory socialization, job applicants realized visibility and persistence in relation to institutional and individualized socialization. During encounter, new employees managed personal and professional life boundaries carefully against the association and visibility affordances. Although some participants used both public and enterprise social media for obtaining job‐related information and understanding coworkers and company culture, during metamorphosis, most interviewees adopted passive information seeking strategies and experienced a paradoxical tension between the enabling and constraining affordances of social media. Findings are discussed with regards to employees’ exertion of agency in managing their professional impressions and coping with high levels of uncertainty and vulnerability during early stages of socialization.     

A destination imagery processing model: Structural differences between dream and favourite destinations

The present paper aims at understanding how destination imagery is processed in tourists’ working memory. The research focuses on two highly desirable, but contrasting, destination brand categories: Favourite Destination, which involves retrospective memory of positive experiences in situ; and Dream Destination, based on tourists’ prospective memory. Through an online multilingual survey, 23,446 responses consisting of perceptions, evoked by way of free-recall, associated to Dream and Favourite Destinations, were collected. Findings point to clear structural differences between the imagery of Dream and Favourite Destinations. Additionally, a theoretical destination imagery model that offers a basis for future studies is proposed, and some managerial implications of significant relevance to destination marketing are discussed.     

COMPARING PPP WITH TRADITIONAL PROCUREMENT: THE CASE OF SCHOOLS PROCUREMENT IN IRELAND

Advocates of public‐private partnerships (PPPs) argue that they can deliver public infrastructure more efficiently than traditional procurement through timelier completion and superior value for money. Despite these claims comparative analysis of the performance of both procurement methods has received scant attention in the PPP literature to date. This paper addresses this issue by providing an in‐depth, case‐based comparison of PPP versus traditional procurement in the schools sector in Ireland. Through detailed semi‐structured interviews with key stakeholders and an examination of the available documentation, we assess whether the key objectives of using PPP have been achieved. Overall, we find no evidence that PPP leads to faster delivery of infrastructure when the overall procurement process from contract notice to delivery is accounted for. In addition, we find only limited evidence to suggest that PPP results in better value for money.     

Media-Based Sentiment Indices as an Alternative Measure of Consumer Confidence

In this paper, we consider the feasibility of constructing online sentiment indices, using large amounts of media data, as an alternative to the conventional survey method used to create the consumer confidence index in South Africa. A clustering framework is adopted to provide an indication of possible candidate sentiment indices constructed from a combination of different text sources and dictionaries that best mimic the traditional survey-based consumer confidence index from the South African Bureau for Economic Research (BER). The results conclude that it is possible to create an index using sentiment analysis using online editorial data that does resemble the BER’s consumer confidence index. The different media-based sentiment indices (MSI) show a significant level of correlation and co-movement with the BER’s CCI. Impulse responses and cross-correlation functions indicate that the MSI could potentially lead the survey-based method up to two quarters. Furthermore, Granger-causality tests show that the media-based indices are good predictors of future consumer confidence index values. The results provide motivation for further study on the use of sentiment-based techniques and online media data sources to track consumer confidence within an emerging market such as South Africa.     

Why principals tolerate biases of inaccurate agents

Some agents are more accurate than others in estimating the best policy. The more accurately an agent estimates a policy's effects, the more he will resist biases, such as bribes from a special interest. Thus, a special interest needs to pay a larger bribe to an accurate agent than to an inaccurate agent. The accurate agent who is biased will then more likely cause harm than does an inaccurate agent who favors the special interest. Therefore, the principal may gain more from controlling biases of an accurate agent than of an inaccurate one. Thus, high ability of public officials may be associated with little corruption.     

Sustaining brand loyalty: The moderating role of green consumption values

Environmental issues are massively emerging in the current agendas of governments, businesses and consumers all over the globe. Consumers increasingly adopt a more energetic role in the environmental discussion and employ product consumption to manifest their contribution to the debate. Equally, a growing number of businesses try to affect positive social change, whereas others strategically approach green opportunities; at the same time, they persistently intensify their branding offerings to sustain loyalty. This article brings into discussion green consumption values as the authors aim to shed light into the way the latter moderate the effect of brand related factors, namely, brand experiences and brand personality, on brand loyalty. Based on data received from 413 participants and using the wearable technologies industry as the focal context, the study underscores the significance of green consumption values. Findings are discussed, and implications for managers are provided.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Cross‐Functional Integration: Concept Clarification and Scale Development

The centrality of cross‐functional integration (CFI) to supply chain theory and practice has long been recognized. Yet researchers continue to struggle with consistently defining or measuring the CFI construct, thus limiting the utility of CFI research. This research develops (1) a comprehensive definition of CFI that synthesizes previous supply chain research and (2) a valid set of scale items that measure the conceptual domain outlined by this definition. The goal is to build a common foundation for extending knowledge on CFI's antecedents and consequences, and ultimately to improve scholars’ ability to guide a broader practitioner community still struggling to achieve integration in their organizations.     

A hybrid information approach to predict corporate credit risk

This study proposes a hybrid information approach to predict corporate credit risk. In contrast to the previous literature that debates which credit risk model is the best, we pool information from a diverse set of structural and reduced‐form models to produce a model combination based on credit risk prediction. Compared with each single model, the pooled strategies yield consistently lower average risk prediction errors over time. We also find that while the reduced‐form models contribute more in the pooled strategies for speculative‐grade names and longer maturities, the structural models have higher weights for shorter maturities and investment grade names.