THE USE OF SOCIAL NETWORK ANALYSIS IN LOGISTICS RESEARCH

This paper introduces and provides an overview of social network theory and social network analysis (SNA) and its potential applications to logistics and supply chain management research. It then provides an example of the use of SNA via the introduction of hypotheses related to informal and formal structure and influence within a social network. These hypotheses are tested within the context of the development and implementation of a complex reporting system that evolved as the result of warehousing safety and environmental concerns within an organization.     

Economic complexity,product space network and Quebec's global competitiveness

This exploratory study uncovers how the economic complexity of local production and global connectivity contribute to a subnational region's competitiveness and sustainable development. Addressing the knowledge generation and exchange processes orchestrated by global value chains, we demonstrate that the composition of a subnational region's product space network does not necessarily replicate the same configuration of the country-level network. By applying social network analysis (SNA) techniques, we analyze the structural features of Quebec's product space network and compare the complexity indices of the province's advantageous sectors with those of Canada. Finally, we conclude with policy insights for sustainable development and suggest future research directions.     

Historical social network analysis: Advancing new directions for international business research

Despite repeated calls for incorporating history in IB research, progress has been slow. The few existing IB studies utilizing historical approaches have relied mostly on historical narrative approaches. In addition, there is little methodological guidance on how to use historical methodologies in IB research. This article will highlight a growing methodological approach for consideration, one that demonstrates intersections across multiple disciplines through use of varied techniques, historical analysis and social network analysis (SNA) and source-bases (varied archival sources). This study will demonstrate the richness obtained from utilising historical source collections and the additional perspectives on transnational networks that can be obtained from analysing networks over longer periods. Specifically, we argue that the use of historical mixed methods SNA is suitable in addressing calls for contextual, longitudinal, multilevel, and processual explanations of IB phenomena.     

Content Strategies for Digital Consumer Engagement in Social Networks: Why Advertising Is an Antecedent of Engagement

Advertisers need to optimize their efforts on social networks to engage consumers effectively. Existing literature on this topic has not yet explained how social network advertising (SNA) can be categorized into different content types and how to conceptualize and operationalize digital consumer engagement (DCE) in social networks. Thus, we derive seven content categories for social network advertising and a four-level model for DCE based on consumers' intermediate mind-set responses. We propose the impact of different SNA categories as an antecedent of DCE. Our results confirm a significant but unequal impact of at least four content categories on various engagement metrics. We therefore distill the successful content strategies and content attributes for specific types of engagement and confirm intermediate responses to advertising in a real market situation.     

Organizing a precarious black box: An actor‐network account of the Atlantic Schools of Business, 1980–2006

There is a growing use of actor‐network theory (ANT) throughout management and organization studies. While earlier ANT research used ethnography to “follow the actors” in the production of organization/knowledge, more recent studies use archival sources to examine developments over time. We extend the latter approach using qualitative social network analysis (SNA) and apply this to a case study of the Atlantic Schools of Business (ASB). Our contribution is two‐fold: first, through an examination of actors in the ASB networking processes over 26 years, we demonstrate how the seemingly stable surface of an organization can hide the precariousness of organizing; second, we reveal the potential fusion of ANT with SNA as a method for dealing with large qualitative datasets over long periods of time. Copyright © 2015 ASAC. Published by John Wiley & Sons, Ltd.     

Process Coordination Within a Health Care Service Supply Network

There are two manifestations of supply chains in health care. One involves the supply of equipment and materials used in health care delivery. The other supply chain involves the delivery of health care itself, wherein patients supply their physical conditions and service suppliers deliver health care services. This article considers the latter supply chain, analyzing a case study in which patients have comorbidities and thus require the services of a network of multiple health care providers. In the case study, we examine three schemes for coordination of care. In the first scheme, the patient herself is expected to manage the coordination. In the second scheme, physicians are expected to coordinate the care. In the third scheme, a third‐party coordinator manages care across network members. We examine these three possible coordination alternatives using a technique known as Process‐Chain‐Network (PCN) Analysis. PCN Analysis helps us document how coordination schemes are implemented and where they may fail. Our analysis of the case study leads us to the development of ex post theory about who should initiate coordination and how it should take place under conditions of comorbidities. Empirical data coming from the case study support the theory. We describe possible applications of the theory inside and outside of health care, and show how the PCN approach can guide process innovation.     

Social Network Analysis and Communication in Emergency Response Simulations

In this article, social network analysis (SNA) is applied on two emergency responses, involving chemical, biological, radiological, nuclear, and explosives (CBRNE) simulations. However, SNA has seldom been used in the literature to explain communication breakdowns, leading to the question of “can it?” To examine the applicability of SNA when assessing communication, the SNAs of two CBRNE simulations are compared and the structural differences are related to instances of ineffective communication. Study 1 has two tiers in the response (commanders and first responders) and Study 2 has three tiers, where operations officers are added between the commanders and first responders. A higher percentage of communication breakdowns is found in Study 2, possibly as a result of the additional layer. SNA provides researchers with a convenient representation and summary of team functioning. However, basic SNA does not help researchers distinguish between effective communication and breakdown. Breakdowns are attributed to long multi-hop communications, attributable to larger networks.     

Interactive Mining of Strong Friends from Social Networks and Its Applications in E-Commerce

Social networks are generally made of individuals who are linked by some types of interdependencies such as friendship. Most individuals in social networks have many linkages in terms of friends, connections, and/or followers. Among these linkages, some of them are stronger than others. For instance, some friends may be acquaintances of an individual, whereas others may be friends who care about him or her (e.g., who frequently post on his or her wall). In this study, we integrate data mining with social computing to form a social network mining algorithm, which helps the individual distinguish these strong friends from a large number of friends in a specific portion of the social networks in which he or she is interested. Moreover, our mining algorithm allows the individual to interactively change his or her mining parameters. Furthermore, we discuss applications of our social mining algorithm to organizational computing and e-commerce     

RETRACTED ARTICLE: Modern Business Ethics Research: Concepts,Theories, and Relationships

The main purpose of this study is to explore and map the intellectual structure of business ethics studies during 1997–2006 by analyzing 85,000 cited references of 3,059 articles from three business ethics related journals in SSCI and SCI databases. In this article, co-citation analysis and social network analysis techniques are used to research intellectual structure of the business ethics literature. We are able to identify the important publications and the influential scholars as well as the correlations among these publications by analyzing citation and co-citation. Three factors emerged in this study are: (1) ethical/unethical decision making, (2) corporate governance and firm performance, and (3) ethical principles and code of conduct.     

Determining perceptions,attitudes and behaviour towards social network site advertising in a three-country context

ABSTRACT

Regardless of the growth in social media and social network advertising (SNA), little theoretical and empirical knowledge exists on the differences between countries, and the perceptions and attitudes towards social network advertising. The purpose of the study is to investigate the relationships between users’ perceptions (personal and societal), their attitudes and their behaviour towards Facebook advertising, across three countries, as well as the moderating role of privacy and general advertising attitudes. Online surveys were administered and a convenience sampling resulted in 1,166 respondents. Structural equation modelling was used to test the proposed model.

The research indicates that the social support theory shows promise for examining the perceptions and attitudes towards SNA. Furthermore, the validity of the conceptual model is confirmed in all three countries; however, the strength of these relationships differs. Additionally, it is evident that consumers’ culture influences the role of privacy and trust in SNA perceptions.     

Peer-to-Peer Value Through Social Capital in an Online Motor Neuron Disease Community

Millions of people affected by disability or chronic disease access social support and information through online health communities. These communities of common interest flourish on the Internet, with participants creating peer-to-peer value through social support and information exchange. This study observes a community of people affected by motor neuron disease creating value for themselves and each other within an online health community. The community is studied through the lens of social capital theory, a construct borrowed from the field of sociology that contributes to our understanding of why people gravitate towards these online communities for support and information. The results contribute increased awareness of how peer-to-peer value is created within online health communities and highlight the need for marketers to understand the implications of such communities on consumer behavior as it relates to health care.     

Stakeholder Perspectives on CSR of Mining MNCs in Argentina

This article examines the conceptualisation of corporate social responsibility (CSR) in the context of mining multinationals (MNCs) in Argentina. It explores the suitability of CSR for addressing social, environmental and economic issues associated with mining in the country. The study is based on interviews with four stakeholder groups in the country: government, civil society, international financial organisations, and mining industry. These are analysed using content and interpretative techniques and supplemented by the content analysis of secondary data from headquarters of mining MNCs. Using the concept of corporate social responsibility orientation (CSRO), the study contrasts the perceptions of major stakeholders and examines adaptation of mining companies’ CSRO to local context. It reveals that the CSRO of mining managers in Argentina differs from CSRO developed by global headquarters; and in Argentina companies “negotiate” economic, environmental and legal dimensions of CSR with the government. Although companies “negotiate” philanthropic responsibilities with the communities, ethical responsibilities are defined by the headquarters and not negotiated locally. The analysis suggests that environmental duties are the critical element of CSR in the mining sector in Argentina. This study treats environment as a separate dimension of corporate responsibility defined as to do “what is safe for the environment”.     

A Proposed Model for Consumer-Based Brand Equity Analysis on Social Media Using Data Mining and Social Network Analysis

Online social networks have expanded their “virtual borders,” making the Internet more like an environment of social interaction than a business tool. However, even before the emergence and expansion of social media, marketing professionals were interested in identifying consumers' perceptions about brands. Thus, operational models have been proposed to facilitate such a task. Those models, however, can be expensive and inconvenient, since the models use questionnaires for data collection. To help overcome this problem, this article proposes a model for brand equity analysis from the consumer perspective expressed in social networks using opinion mining techniques and social network analysis. The application of the proposed model on data collected from Twitter made it possible to analyze five brand equity dimensions: brand awareness, brand loyalty, perceived sentiment, perceived quality, and brand associations. The results reached by the application of the model show that brand equity can be analyzed from data retrieved from virtual social networks, disclosing how consumers perceive brands in such an environment, without using questionnaires, enabling different brands in different contexts. Those data can be analyzed under both objective and replicable criteria for each of the brand equity elements that make up the model.     

The Limits of Corporate Social Responsibility: Techniques of Neutralization, Stakeholder Management and Political CSR

Since scholarly interest in corporate social responsibility (CSR) has primarily focused on the synergies between social and economic performance, our understanding of how (and the conditions under which) companies use CSR to produce policy outcomes that work against public welfare has remained comparatively underdeveloped. In particular, little is known about how corporate decision-makers privately reconcile the conflicts between public and private interests, even though this is likely to be relevant to understanding the limitations of CSR as a means of aligning business activity with the broader public interest. This study addresses this issue using internal tobacco industry documents to explore British-American Tobacco’s (BAT) thinking on CSR and its effects on the company’s CSR Programme. The article presents a three-stage model of CSR development, based on Sykes and Matza’s theory of techniques of neutralization, which links together: how BAT managers made sense of the company’s declining political authority in the mid-1990s; how they subsequently justified the use of CSR as a tool of stakeholder management aimed at diffusing the political impact of public health advocates by breaking up political constituencies working towards evidence-based tobacco regulation; and how CSR works ideologically to shape stakeholders’ perceptions of the relative merits of competing approaches to tobacco control. Our analysis has three implications for research and practice. First, it underlines the importance of approaching corporate managers’ public comments on CSR critically and situating them in their economic, political and historical contexts. Second, it illustrates the importance of focusing on the political aims and effects of CSR. Third, by showing how CSR practices are used to stymie evidence-based government regulation, the article underlines the importance of highlighting and developing matrices to assess the negative social impacts of CSR.     

The impact of pronoun choices on consumer engagement actions: Exploring top global brands' social media communications

To enhance the understanding of consumer engagement with brand content on social media, this study examines how pronoun choices affect different types of consumer engagement (e.g., likes, comments, shares) by simultaneously exploring five different pronoun types (first-person singular, first-person plural, second person, third-person singular, and third-person plural). Furthermore, this study explores how the effects of these linguistic (pronoun) choices vary across two brand classifications: characteristics (hedonic vs. utilitarian) and offerings (goods vs. services). The proposed multivariate Poisson regression model, analyzing 15,788 unique brand posts from Facebook over an 8-month period, reveals differences in engagement due to pronoun usage across brand classifications. These results offer a deeper understanding of how the way brands talk to consumers on social media platforms influences consumers' attitudes (likes), propensity to engage with the brand (comments), and willingness to share branded content with their social networks (shares) across different brand classifications.     

In bot we trust: A new methodology of chatbot performance measures

Chatbots are used frequently in business to facilitate various processes, particularly those related to customer service and personalization. In this article, we propose novel methods of tracking human-chatbot interactions and measuring chatbot performance that take into consideration ethical concerns, particularly trust. Our proposed methodology links neuroscientific methods, text mining, and machine learning. We argue that trust is the focal point of successful human-chatbot interaction and assess how trust as a relevant category is being redefined with the advent of deep learning supported chatbots. We propose a novel method of analyzing the content of messages produced in human-chatbot interactions, using the Condor Tribefinder system we developed for text mining that is based on a machine learning classification engine. Our results will help build better social bots for interaction in business or commercial environments.     

Investigating Organizational Learning through Social Network Analysis: The Case of a Consultancy Firm in India

Three problems beset the literature on organizational learning—confusion about who learns (individuals, groups, or organization), absence of a robust theory, and tools for measurement. Social network analysis, it is argued, can be used to capture organizational learning at multiple levels, to capture relational data (expressed as linkages between actors), and can yield actionable insights for changes within the organization. Two subprocesses of organizational learning, information acquisition and distribution, were measured using social network analysis in a decade‐old consultancy firm in India. Results reveal who shares information with whom, who goes to whom for information, who is bypassed, who hoards, how groups interact, and how much information is shared at the organizational level. The study provides a deeper understanding of how “people” relationships affect learning at various levels. The theoretical and managerial implications of the approach taken to measure organizational learning using social network analysis are discussed. © 2016 Wiley Periodicals, Inc.     

The effect of social media communication on consumer perceptions of brands

Researchers and brand managers have limited understanding of the effects social media communication has on how consumers perceive brands. We investigated 504 Facebook users in order to observe the impact of firm-created and user-generated (UG) social media communication on brand equity (BE), brand attitude (BA) and purchase intention (PI) by using a standardized online survey throughout Poland. To test the conceptual model, we analyzed 60 brands across three different industries: non-alcoholic beverages, clothing and mobile network operators. When analyzing the data, we applied the structural equation modeling technique to both investigate the interplay of firm-created and user-generated social media communication and examine industry-specific differences. The results of the empirical studies showed that user-generated social media communication had a positive influence on both brand equity and brand attitude, whereas firm-created social media communication affected only brand attitude. Both brand equity and brand attitude were shown to have a positive influence on purchase intention. In addition, we assessed measurement invariance using a multi-group structural modeling equation. The findings revealed that the proposed measurement model was invariant across the researched industries. However, structural path differences were detected across the models.     

The competitive solution and the health care problems of today

Mark Pauly claims that a "competitive" health care system will solve the health care cost crisis. This article examines how well the competitive solution deals with the five central problems of the health care system: (1) almost universal lack of adequate health insurance for nursing homes and home care; (2) Medicaid's penurious approach to payment for health services for the poor; (3) the emergence of a dual health care system, especially for children; (4) the entrenched waste and inefficiency of the health care system; and (5) consumers' inability to judge the quality of health care. The competitive solution does not eliminate any of these problems--and may not even improve some of them.