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This study aims to analyze the role of corporate social responsibility (CSR) customer perceptions, customer–company identification and customer trust on customer engagement (CE), paying special attention to the moderating effects of two types of social media communication, firm-generated content and user-generated content.

The study uses a mixed-methods’ approach. First, a single-factor experiment using Twitter posts as stimuli with 227 hotel guests. The structural model was analyzed using SmartPLS 3.2.7. Second, structured in-depth interviews were undertaken with three hotel industry experts to complement the conclusions of the quantitative study.

The results show that when a customer trusts a hotel and identifies with its corporate values, CSR tweets generate CE toward the hotel. CSR communications made by customers reinforce the impact of CSR tweets on customer trust more than CSR tweets posted by hotels. Hotel industry experts give insights to explain these results in different types of hotels.

CSR communications made through Twitter affect customers’ perceptions of a hotel’s CSR activities and customer trust in hotels, especially if they originate from a source external to the company. This result can be of use for hotel managers who have not previously given importance to active CSR communications or the interactivity of social media.

The authors show the moderating effect of user-generated content in the relationship between CSR customer perceptions and customer trust, thus contributing to the research into the effectiveness of social media. They use a mixed-methods’ approach to increase the validity of the results.

Este estudio analiza el papel de las percepciones de RSC, la identificación cliente-empresa (CCI) y la confianza en el engagement del cliente (CE), prestando especial atención al efecto moderador de dos tipos de comunicación en redes sociales: Contenido Generado por la Empresa (FGC) y Contenido Generado por el Usuario (UGC).

Se emplean métodos mixtos: un experimento de un factor usando publicaciones de Twitter como estímulo con 227 huéspedes del hotel, cuyo modelo estructural se analizó con SmartPLS 3.2.7., y 3 entrevistas en profundidad con expertos de la industria hotelera.

Los resultados muestran que, cuando un cliente confía en el hotel y se identifica con sus valores corporativos, los tweets de RSC generan engagement. La comunicación de RSC emitida por usuarios refuerza el impacto de los tweets de RSC en la confianza del cliente más que los tweets publicados por hoteles. Los expertos de la industria hotelera aportan nociones para explicar estos resultados en diferentes tipos de hoteles.

La comunicación de RSC realizada a través de Twitter afecta las percepciones del cliente sobre las actividades de RSC del hotel y la confianza en el mismo, especialmente si proceden de una fuente externa a la empresa. Este resultado puede ser útil para gerentes de hoteles que no se benefician de la comunicación activa de RSC o la interactividad de las redes sociales.

Se valida el efecto moderador del UGC en la relación entre las percepciones de RSC y la confianza de los clientes, contribuyendo así a la investigación sobre la efectividad de las redes sociales. Se emplea un diseño mixto para incrementar la validez de los resultados.

Comunicación de RSC, Engagement del Consumidor, Fuente del mensaje, Contenido generado por la empresa, Contenido generado por el usuario, Twitter, Compromiso con el cliente

Trabajo de investigación

There is an ongoing challenge to map the efficacy of e-retailing strategies in building both value co-creation opportunities for online customers and customer value for companies. Based on the service-dominant (S-D) logic, an integrative model is provided that connects the impact of convenience and personalisation strategies (CPSs) on an e-retailer's performance – by offering co-creation opportunities and customer engagement.

The survey instrument is validated and the model is tested with data from active online customers using a novel methodology that blends artificial neural network (ANN) analysis with partial least squares (PLS) in both the measurement model and the path analysis.

The findings robustly support the model and yield evidence of the contribution of CPSs in effective value propositions, the interface between the S-D logic and customer engagement, and the direct effect of customer engagement on tangible forms of value for companies.

This study is the first scholarly effort to provide a comprehensive understanding of how and why CPSs can maximise customer value for the e-retailer, while simultaneously testing the customer value/engagement interface with a new blended ANN-PLS method.

The purpose of this study is to address two issues relevant to those managing product returns: (1) how customers perceive the returning process and assessing the extent that these perceptions have on satisfaction with the organization, loyalty and word-of-mouth (WOM) and (2) are these outcomes moderated by whether customer returns were planned or unplanned?

The data consisted of 21 semi-structured interviews (pilot study) and a quantitative survey (n = 384; main study) targeted at consumers who had bought fashion items online.

Qualitative insights revealed that perceptions of the returning experience are driven by monetary costs, convenience, stress and guilt. Quantitative findings showed that the returning experience explains return satisfaction for both planned and unplanned returners, and returning satisfaction explains overall satisfaction and WOM. The noteworthy difference concerns loyalty: although customers that planned to return items are more loyal to the organization, it is the unplanned returners whose loyalty can be significantly increased by better managing the returning process.

Returning products online is increasingly common and thus forms an important part of the customer's overall experience with an organization. Returns management can therefore drive key customer outcomes. Understanding the dynamics between the product return experience, return satisfaction and customer outcomes will help practitioners design and implement more informed returns management strategies. Measures are also presented that assess the cognitive and emotional aspects associated with returning products.

Returning products is an increasingly important challenge for online retailers. Understanding what kinds of returning behaviors occur allows companies to design and execute better informed decisions to manage this phenomenon, not only for the sake of firm performance but also for societal and environmental benefits – the triple bottom line.

While scholars have investigated the relationship between return policies (e.g. free vs fee) and profitability, no prior literature has examined the returning experience: how consumers perceive the returning process; motivations for their returns (whether returns were planned or not) and subsequent customer outcomes.

The purpose of this study is to present and explain a new customer segmentation approach inspired by failure mode and effect analysis (FMEA) which can help classify customers into more accurate segments.

The present study offers a look at the three most commonly used approaches to assessing customer loyalty:net promoter score, loyalty ladder and loyalty matrix. A survey on the quality of restaurant services compares the results of categorizing customers according to these three most frequently used approaches.

A new way of categorizing customers through loyalty priority number (LPN) is proposed. LPN was designed as a major segmentation criterion consisting of customer loyalty rate, frequency of purchase of products or services and value of purchases. Using the proposed approach allows to categorize customers into four more comprehensive groups: random, bronze, silver and gold – according to their loyalty and value to the organization.

Survey will bring a more accurate way of categorizing customers even in those sectors where transaction data are not available. More accurate customer categorization will enable organizations to use targeting tools more effectively and improve product positioning.

The most commonly used categorization approaches such as net promoter score, loyalty ladder or loyalty matrix offer relatively general information about customer groups. The present study combines the benefits of these approaches with the principles of FMEA. The case study not only made it possible to offer a view of the real application of the proposed approach but also made it possible to make a uniform comparison of the accuracy of customer categorization.

Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.

Digital technologies have fundamentally changed organizations, industries, and even the society. Although institutional theory provides rich array of perspectives to both the content and dynamics of such changes, research at the intersection of institutional scholarship and digitalization has remained scarce. In this essay, I draw on the institutional logics perspective to elaborate digitalization as involving a new set of interconnected managerial beliefs and norms, organizational practices, and diverse material and social structures that together complement and challenge the established logics in organizations and institutional fields. I draw attention to two central organizing principles in the logic of digitalization: the pursuit of digital omniscience – the efforts to represent and conceive the world through digital data – and digital omnipotence – the efforts to bring activities inside and outside organizations under the control of information systems. I conclude the essay by elaborating how the institutional logics perspective can help understand organization-level efforts to leverage digitalization by incumbent corporations and new digital-native companies.