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There is ample empirical evidence in the literature for the positive effect of central bank transparency on the economy. The main channel is that transparency reduces the uncertainty regarding future monetary policy and thereby it helps agents to make better investment and saving decisions. In this chapter, we document how the degree of transparency of central banks in Central and Eastern Europe has changed during periods of financial stress, and we argue that during the recent financial crisis central banks became less transparent. We investigate also how these changes affected the uncertainty in these economies, measured by the degree of disagreement across professional forecasters over the future short- and long-term interest rates and also by their forecast accuracy.

The purpose of this paper is to present exciting and innovative research questions in service operations that are aligned with eight key themes and related topics determined by the Journal of Service Management (JOSM) Service Operations Expert Research Panel. By offering a good number of such research questions, this paper provides a broad range of ideas to spur conceptual and empirical research related to service operations and encourage the continued creation of deep knowledge within the field, as well as collaborative research across disciplines that develops and incorporates insights from service operations.

Based on a Delphi study, described in the companion article, “Service Operations: What Have We Learned?,” the panel identified eight key research themes in service operations where leading-edge research is being done or has yet to be done (Victorino et al., 2018). In this paper, three or four topics within each theme are selected and multiple questions for each topic are proposed to guide research efforts. The topics and questions, while wide-ranging, are only representative of the many ongoing research opportunities related to service operations.

The field of service operations has many interesting research topics and questions that are largely unexplored. Furthermore, these research areas are not only increasingly integrative across multiple themes within operations but often transcend functional disciplines. This creates opportunities for ever more impactful research with a greater reach throughout the service system and suggests that service researchers, regardless of functional affiliation, can contribute to the ongoing conversation on the role of service operations in value creation.

Leveraging the collective knowledge of the JOSM Service Operations Expert Research Panel to expand on the research themes generated from the Delphi study, novel questions for future study are put forward. Recognizing that the number of potential research questions is virtually unlimited, summary questions by theme and topic are also provided. These questions represent a synopsis of the individual questions and can serve as a quick reference guide for researchers interested in pursuing new directions in conceptual and empirical research in service operations. This summary also serves as a framework to facilitate the formulation of additional research topics and questions.

The purpose of this paper is to explain the direct and moderating effects of perceived transparency on citizen satisfaction with public healthcare services.

This paper extends the classic framework of service quality, value and satisfaction by adding perceived transparency as an essential component, applies service-dominant logic to develop hypotheses regarding the effects of transparency and empirically tests the extended framework with secondary household survey data on China’s public healthcare.

The classic framework of service quality, value and satisfaction that originated from the private sector is robust in public service. Perceived transparency has a positive impact on perceived value and citizen satisfaction, but the positive effects of service quality and perceived value on citizen satisfaction were weakened with the increasing level of perceived transparency.

Perceived transparency is a double-edged sword regarding citizen satisfaction: although transparency increases perceived value and satisfaction by enhancing citizens’ service co-creation and inspiring citizen confidence, increased transparency raises citizens’ expectations for service products, which subsequently dampens the positive effects of service quality and perceived value on citizen satisfaction.

In a context with higher transparency, local authorities must learn to manage citizen expectations that influence satisfaction, and increase the probability of satisfaction by avoiding too high citizen expectations.

This paper highlights the importance of transparency in enhancing public service co-creation, and contributes a novel perspective on the effects of transparency in the formation of citizen satisfaction, which may serve as the starting point for studying the role of transparency in public affairs.

In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.

This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.

This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.

This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.

Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.

The evidence concerning the effects of the inflation targeting (IT) regime as well as greater central bank transparency on monetary policy interest rates is not conclusive, and the following questions remain open. What is the effect of adopting IT on both the level and volatility of monetary policy interest rate? Does central bank transparency affect the level of the monetary policy interest rate and its volatility? Are these effects greater in developing countries? The purpose of this paper is to contribute to the literature by answering these questions. Hence, the paper analyzes the effects of IT and central bank transparency on monetary policy.

The analysis uses a sample of 48 countries (31 developing) comprising the period between 1998 and 2014. Based on panel data methodology, estimates are made for the full sample, and then for the sample of developing countries.

Countries that adopt the IT regime tend to have lower levels of monetary policy interest rates, as well as lower interest rate volatility. The effect of adopting IT on both the level and volatility of the basic interest rate is smaller in developing countries. Besides, countries with more transparent central banks have lower levels of monetary policy interest rates, as well as lower interest rate volatility. In turn, the effect of central bank transparency on both the level and volatility of the basic interest rate is greater in developing countries.

The study brings important practical implications regarding the influence of both the IT regime and central bank transparency on monetary policy.

Studies have sought to analyze whether IT and central bank transparency are effective to control inflation. However, few studies analyze the influence of IT and central bank transparency on interest rates. This study differs from the few existing studies since: the analysis is done not only for the effect of transparency on the level of the monetary policy interest rate, but also on its volatility; the central bank transparency index that is used has never been utilized in this sort of analysis; and the study uses panel data methodology, and compares the results between different samples.

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

Supply chain integration (SCI) dominates supply chain strategy and is receiving increasing academic attention. The purpose of this paper is to provide a systematic review of the knowledge trajectory and structure of the SCI field.

Based on 3,533 papers extracted from the Web of Science (WoS), this paper adopts the main path analysis (MPA) method to detect three distinct knowledge development trajectories. Coupling-based clustering is combined with MPA to reveal three critical subfields.

The findings show that the definition, content and dimensions of SCI lack unified conclusions. The influencing factors and performance consequences of SCI are long-standing research elements. Building theoretical models and integrated systems and applying blockchain technology to improve SCI are the key research contents. The intertwining of collaboration and SCI cannot be ignored, and the green SCI may be a hot topic in the future.

This study explores knowledge in the SCI field based on the limited literature collected by WoS rather than all published papers. The omissions of some relevant papers and books may exist.

The study methodology provides a framework for similar studies in the future, and the results help researchers to get a comprehensive picture of the knowledge trajectory and structure of the SCI field.

Compared to existing reviews, MPA combines cluster analysis to develop a synthetic framework of the knowledge trajectory and structure in the SCI domain. It contributes to a systematic review of the development of SCI.

The business operations of today's enterprises are heavily influenced by numerous of internal and external business events. With the Event Driven Architecture and particularly the Complex Event Processing (CEP), the technology required for identifying complex correlations in these large amounts of event data right after its appearance has already emerged. The resulting gain in operational transparency builds the foundation for (near) real-time reactions. This motivated extensive research activities especially in the field of Business Process Management (BPM), which essentially coined the term Event-Driven BPM (EDBPM). Now, several years after the advent of this new concept, the purpose of this paper is to shed light to the question: where are we now on our way towards a sophisticated adoption of the CEP technology within BPM?

The research methodology of this paper is a structured literature analysis. It basically follows the procedure proposed by vom Brocke et al. (2009). This verified five-step process – entitled “Reconstructing the giant” – allowed a rigorous study. As a result, various research clusters were derived, whose state-of-the-art exposed existing research gaps within EDBPM.

First of all, the paper provides a concise conceptual basis on different application possibilities of EDBPM. Afterwards, it synthesizes current research into six clusters and highlights most significant work within them. Finally, a research agenda is proposed to tackle existing research gaps to pave the way towards fully realizing the potentials of the paradigm.

So far, a comparable study of the current state-of-the-art within EDBPM is non-existent. The findings of this paper, e.g. the proposed research agenda, help scholars to focus their research efforts on specific aspects that need to be considered in order to advance the adoption of the CEP technology within BPM.