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Although trade volumes in e-retailing have increased significantly in recent years, logistics service failures are inevitable, especially at the delivery stage. Therefore, it is essential to provide customers with effective recovery strategies to increase their satisfaction and repurchase intentions. There is a lack of empirical evidence on whether the response time or the discount offered in compensation is more crucial for customers. Therefore, this study aims to determine whether the response time or the discount offered for high and low criticality failures has a greater impact on customer satisfaction levels and repurchase intentions for female and male customers.

A scenario-based experimental design method has been adopted to collect data, and 697 participants aged 18 and 58 years have been reached. The research utilized a between-subjects design, incorporating three factors: gender (female vs male), criticality (high vs low) and compensation (7 days: 10% discount, 10 days: 20% discount and 14 days: 30% discount). Six scenarios depicting the failure of an online retailer were created, and factorial univariate ANOVA was conducted to test the hypotheses.

The study's results show that in terms of customer satisfaction, female customers attach more importance to the response time in the case of high criticality and the amount of discount offered in the case of low criticality. On the other hand, male customers give more importance to the response time in terms of customer satisfaction when they experience a high or low criticality failure. In the case of low criticality, response time is more important for male customers to increase their repurchase intentions, while the amount of the discount is more important for female customers.

The study demonstrates the relative importance of the response time and discount amount according to the criticality level of failures and to guide business managers in terms of the recovery strategies they will implement. It focuses on gender differences and determine whether the response time or discount amount is more important for male and female customers in high or low-criticality situations.

How does business model design play a role in enabling manufacturing firms’ services? This study aims to investigate the impact of two distinct types of business model design, namely, efficiency-centered business model design (EBMD) and novelty-centered business model design (NBMD), and their effects in balanced and imbalanced configurations, on two types of services: product- and customer-oriented services.

Using matched survey data of 390 top managers and objective performance data of 195 Chinese manufacturing firms, this study uses hierarchical regression, polynomial regression and response surface analysis to test the hypotheses.

The results show that while EBMD positively affects product-oriented services, NBMD positively affects customer-oriented services. Both types of services exert a significant influence on firm performance. Furthermore, the degree of product- and customer-oriented services increases with an increasing effort level with a balance between EBMD and NBMD. Asymmetrical, imbalanced configuration effects reveal that the degree of product-oriented services is higher when the EBMD effort exceeds the NBMD effort, and the degree of customer-oriented services is higher when the NBMD effort exceeds the EBMD effort.

This study enriches the understanding of designing business models to facilitate service growth in manufacturing firms, ultimately benefiting firm performance. In addition, exploring balanced and imbalanced configurations of EBMD and NBMD offers new insights into business model dual design research.

This chapter reviews new technologies, new types of players and new types of financial products that together are fundamentally affecting supply and demand dynamics in the financial sector and contributing to the emerging digital financial landscape. The aim of this chapter is to set a common understanding on the underlying forces of digital disruption in the financial sector before exploring the challenges to monetary and financial stability that are arising. In later chapters, the book will examine how central banks might deal with the challenges and help shape the emerging digital financial landscape.

The service environment is becoming increasingly turbulent, leading to calls for a systemic understanding of it as a set of dynamic service ecosystems. This paper advances this understanding by developing a typology of service ecosystem dynamics that explains the varying interplay between change and stability within the service environment through distinct behavioral patterns exhibited by service ecosystems over time.

This study builds upon a systematic literature review of service ecosystems literature and uses system dynamics as a method theory to abductively analyze extant literature and develop a typology of service ecosystem dynamics.

The paper identifies three types of service ecosystem dynamics—behavioral patterns of service ecosystems—and explains how they unfold through self-adjustment processes and changes within different systemic leverage points. The typology of service ecosystem dynamics consists of (1) reproduction (i.e. stable behavioral pattern), (2) reconfiguration (i.e. unstable behavioral pattern) and (3) transition (i.e. disrupting, shifting behavioral pattern).

The typology enables practitioners to gain a deeper understanding of their service environment by discerning the behavioral patterns exhibited by the constituent service ecosystems. This, in turn, supports them in devising more effective strategies for navigating through it.

The paper provides a precise definition of service ecosystem dynamics and shows how the identified three types of dynamics can be used as a lens to empirically examine change and stability in the service environment. It also offers a set of research directions for tackling service research challenges.

The Penrose effect, or the limitation of the growth rate during expansion due to managerial constraints, has been examined in the context of business diversification, withdrawal and MNE’s foreign direct investment, primarily in the for-profit sector. However, insufficient attention has been paid to its impact on professional service firms, particularly in the context of their expansion through service exports. The main purpose of this study is to examine the Penrose effect in the internationalization of professional service firms through service exports.

This study focuses on large Japanese patent firms as traditional professional service firms and constructs panel data for 48 large patent firms over the observation period from 2002 to 2010 to test our hypotheses.

Our results demonstrate a negative relationship between degree of internationalization and international business growth, thus confirming the Penrose effect. Furthermore, we found that the degree of internationalization has a curvilinear relationship with international business growth and that institutional distance does not have a negatively moderating effect on the relationship between the degree of internationalization and international business growth.

This study made a theoretical contribution to Penrose's growth theory and previous studies on international management and professional service firms and international management by showing that the Penrose effect can be observed in the international expansion of professional service firms through service exports. Moreover, this study identifies the factors that modify the Penrose effect, thereby making a significant theoretical contribution.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).

This paper aims to contribute to the management control systems (MCS) changes in public-private partnerships (PPSs) by developing a conceptual archetype explaining the relationship between trust and MCSs in PPPs, and highlighting how this relationship may evolve over time.

The paper adopts a longitudinal case study methodology focusing on a hospital built and operated under a project finance deal. The methods adopted include semistructured interviews, direct observation and internal documentation analysis. We conducted 15 semistructured interviews from 2019 to 2021. In analyzing different documents and interviews, we triangulated data to ensure solid interpretation.

The case shows how trust can take different configurations depending on the type of MCS used. The results highlight how different patterns of MCSs, about trust, can be combined to govern PPPs. The case also shows the temporal dynamics of how MCS and trust evolve at different organizational levels and how bureaucratic control matched with contractual trust and trust-based control matched with competence trust can coexist at different times and organizational levels.

Managers involved in PPPs will be aware of the role of different types of trust in shaping and managing the relationship between partners at different organizational levels. Furthermore, the findings could help policymakers to adopt more informed decisions and to promote practice-based trust at various organizational levels of PPPs.

The paper proposes a management control archetype based on bureaucracy- and trust-based patterns concerning the level of programmability of tasks, as well as defined risks.

In modern societies, consumer well-being is dependent on choices regarding complex services, such as investments, health care, insurance and lending. However, evaluating costs of such services is often difficult for consumers due to a combination of limited cognitive resources and complexity of the service. The purpose of this study is to empirically examine to what extent three specific consequences of complexity influence consumer tendencies to make mistakes when evaluating the costs (or price) of complex services.

Three studies were conducted (survey: n = 153, experiment: n = 332 and conjoint analysis: n = 225), all focusing on how consumers evaluate costs in the complex mutual fund setting.

The authors find that consumers struggle with estimating and using cost information in decision-making in the complex services setting. Consumers of complex services frequently underestimate the costs over the long-term, may see costs as a signal of service quality and are susceptible to influence from presentation formats when evaluating costs.

The study investigates mutual funds, which is one example of a complex service. In order to get a full picture of how consumers deal with costs in complex setting, future research needs to expand this focus to other types of complex services.

The results have implications for both marketers of complex services and policymakers. For marketers, this paper highlights that competing with a low-cost strategy may be difficult in the complex services setting as consumers may lack the ability to actually evaluate what they pay over the long term. For policymakers, increased simplification of prices may be an attractive option. However, it is important that this simplification is done in a way that increases the possibility to compare prices.

As complexity influences several aspects of decision-making, an understanding of how consumers evaluate costs in complex settings is dependent on taking a multidimensional research approach. This paper makes a novel contribution to the literature on pricing by showing that consumers struggle with multiple aspects when evaluating costs in complex contexts. Understanding these effects is important to policy, as well as to research on the cognitive value of simplicity that is currently gaining traction in marketing research.

While the proliferation of chatbots allows companies to connect with their customers in a cost- and time-efficient manner, it is not deniable that they quite often fail expectations and may even pose negative impacts on user experience. The purpose of the study is to empirically explore the negative user experience with chatbots and understand how users respond to service failure caused by chatbots.

This study adopts a qualitative research method and conducts thematic analysis of 23 interview transcripts.

It identifies common areas where chatbots fail user expectations and cause service failure. These include their inability to comprehend and provide information, over-enquiry of personal or sensitive information, fake humanity, poor integration with human agents, and their inability to solve complicated user queries. Negative emotions such as anger, frustration, betrayal and passive defeat were experienced by participants when they interacted with chatbots. We also reveal four coping strategies users employ following a chatbots-induced failure: expressive support seeking, active coping, acceptance and withdrawal.

Our study extends our current understanding of human-chatbot interactions and provides significant managerial implications. It highlights the importance for organizations to re-consider the role of their chatbots in user interactions and balance the use of human and chatbots in the service context, particularly in customer service interactions that involve resolving complex issues or handling non-routinized tasks.

The purpose of this paper is to examine patient engagement in remote consultation services, an increasingly important issue facing Healthcare Operations Management (HOM) given the significant expansion in this and other forms of telehealth worldwide over the last decade. We use our analysis of the literature to develop a comprehensive framework that incorporates the patient journey, multidimensionality, antecedents and consequences, interventions and improvement options, as well as the cyclic nature of patient engagement. We also propose measures suitable for empirical assessment of different aspects of our framework.

We undertook a comprehensive review of the extant literature using a systematic review approach. We identified and analysed 63 articles published in peer-reviewed scientific journals between 2003 and 2022.

We conceptualise patient engagement with remote consultation across three key aspects: dimensions, process, and the antecedents and consequences of engagement. We identify nine contextual categories that influence such engagement. We propose several possible metrics for measuring patient engagement during three stages (before service, at/during service and after service) of remote consultation, as well as interventions and possible options for improving patient engagement therein.

The primary contribution of our research is the development of a comprehensive framework for patient engagement in remote consultation that draws on insights from literature in several disciplines. In addition, we have linked the three dimensions of engagement with the clinical process to create a structure for future engagement assessment. Furthermore, we have identified impact factors and outcomes of engagement in remote consultation by understanding which can help to improve levels of adoption, application and satisfaction, and reduce healthcare inequality. Finally, we have adopted a “cyclic” perspective and identified potential interventions that can be combined to further improve patient engagement in remote consultation.