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To promote the success of peer-to-peer accommodation, this study examines the effects of online host–guest interaction as well as the interaction's boundary conditions of listing price and reputation on listing popularity.

Using 330,686 data collected from Airbnb in the United States of America, the authors provide empirical evidence to answer whether social-oriented self-presentation and response rate influence listing popularity from the perspective of social exchange theory (SET). In addition, the authors investigate how these two kinds of online host–guest interactions work with listing price and reputation to influence listing popularity.

The results reveal the positive association between online host–guest interaction and listing popularity. Notably, the authors find that listing price strengthens but listing reputation weakens the positive effects of online host–guest interactions on listing popularity in peer-to-peer accommodation.

This study is the first attempt to adopt SET to explain the importance of online host–guest interactions in influencing listing popularity as well as examine the moderating role of listing price and reputation on the above relationship.

The authors test the effect of expenditure decentralization and fiscal equalization on short- and long-run economic growth and estimate two-step generalized method of moment (GMM) simultaneous equations models, using panel data for China and India for the period 1985 to 2005. The authors estimate two simultaneous equations: a growth equation and equalization equation and find that expenditure decentralization has a negative and statistically significant effect at conventional levels on short-run economic growth for both China and India. However, the authors also find that this result is sensitive to the set of included explanatory variables. This leads the authors to conclude that expenditure decentralization has no effect on short-run economic growth for either country. The authors also find that expenditure decentralization has a positive and statistically significant effect on fiscal equalization for both countries but find no evidence that fiscal equalization affects short-run economic growth for either China or India. In contrast, the authors find that expenditure decentralization has a positive effect on long-run economic growth in the case of India, but not in the case of China. Finally, the authors report evidence that fiscal equalization has no effect on long-run economic growth in the case of China; however, the authors find that equalization has a positive and statistically significant at conventional levels effect on long-run economic growth in India.

The authors estimate two-step GMM simultaneous equations models, using panel data for China and India for the period 1985 to 2005. To examine the effect of fiscal decentralization (FD) policies on economic growth in China and India, the authors estimate two equations: a growth equation and an equalization equation. For the growth equation, the authors adopt a production-function-based model that is widely used in the empirical literature on growth; however, the authors do make some compromises with this specification due to the unavailability of certain data. For the equalization equation, the authors include variables that economic theory and empirical evidence suggest influence fiscal disparities among subnational governments which in turn influence the demand for horizontal fiscal equalization (HFE). To the extent possible, the authors employ the same econometric specification, variable constructions and sample periods for both China and India. The authors believe this strategy provides a more rigorous test of the FD hypothesis.

The authors find that expenditure decentralization has a negative and statistically significant effect at conventional levels on short-run economic growth for both China and India. However, the authors also find that this result is sensitive to the set of included explanatory variables. This leads to conclude that expenditure decentralization has no effect on short-run economic growth for either country. The authors also find that expenditure decentralization has a positive and statistically significant effect on fiscal equalization for both countries but find no evidence that fiscal equalization affects short-run economic growth for either China or India. In contrast, the authors find that expenditure decentralization has a positive effect on long-run economic growth in the case of India, but not in the case of China. Finally, the authors report evidence that fiscal equalization has no effect on long-run economic growth in the case of China; however, the authors find that equalization has a positive and statistically significant at conventional levels effect on long-run economic growth in India.

Due to the importance of FD policies, especially to many developing countries that are currently pursuing decentralization reforms, future research should examine the effect of FD on economic growth for other countries. Furthermore, although it would be difficult to do so, future research should examine whether FD promotes political stability on ethnically diverse countries.

To the best of the authors’ knowledge, no one has examined the effect of FD policies on India's growth experience. What is more is that this is also the first of its kind to have a comprehensive empirical investigation into these two major developing countries with very interesting similarities and differences in FD policies. It is thus of great importance to examine the effect of expenditure decentralization and HFE on economic growth in China and India.

Weak-form rationality of fixed-event forecasts implies that forecast revisions should not be correlated. However, significant positive correlations between consecutive forecast revisions were found in most USDA forecasts for U.S. corn, soybeans, wheat, and cotton. This study developed a statistical procedure for correction of this inefficiency which takes into account the issue of outliers, the impact of forecast size and direction, and the stability of revision inefficiency. Findings suggest that the adjustment procedure has the highest potential for improving accuracy in corn, wheat, and cotton production forecasts.

This research aims to examine whether the facial appearances and expressions of Airbnb host photos influence guest star ratings.

This research analyzed the profile photos of over 20,000 Airbnb hosts and the guest star ratings of over 30,000 Airbnb listings in New York City, using machine learning techniques.

First, hosts who provided profile photos received higher guest ratings than those who did not provide photos. When facial features of profile photos were recognizable, guest ratings were higher than when they were not recognizable (e.g. faces too small, faces looking backward or faces blocked by some objects). Second, a happy facial expression, blond hair and brown hair positively affected guest ratings, whereas heads tilted back negatively affected guest ratings.

This research is the first, to the best of the authors’ knowledge, to analyze the facial appearances and expressions of profile photos using machine learning techniques and examine the influence of Airbnb host photos on guest star ratings.

The purpose of this paper is to investigate the impact of two types of narcissism (rivalry and admiration) on consumer–brand forgiveness (CBF) following a brand transgression. This research also examines how narcissism interacts with transgression type to shape forgiveness intentions.

Data were collected through an online survey of 634 UK consumers, focussing on two different types of transgressions (public vs private). The formulated hypotheses were tested through moderated mediation analysis.

The results highlight that only narcissistic rivalry (and not admiration) moderates the relationship between transgression type and blame attributions. Although the type of transgression seems to affect CBF, forgiveness levels do not vary across the two transgression types. Finally, as expected, blame attributions shape forgiveness intentions.

The results of this research highlight that blame attributions are affected by the type of narcissism. Thus, identifying the type of narcissism will allow brands to allocate their resources more effectively in order to design recovery strategies that would promote CBF and restore brand trust.

The paper responds to calls for a better understanding of forgiveness through the use of personality traits and focusses on two dimensions of narcissism. This paper also uses a novel transgression typology, which is objective in nature. The results illustrate that narcissism has a differential role in shaping blame attributions and CBF.

The purpose of this paper is to assess whether Europeana can be really seen as the new “Library of Alexandria” for digital resources from the perspective of teachers, academics and researchers that might want to retrieve and reuse those resources for learning purposes.

The authors define a systematic method for studying Europeana digital resources and their potential for reuse in e-learning environments. To achieve this, the authors explore the coverage of digital resources when searching information about a specific area. The paper studies the relevance of the results (thematic coverage) provided by queries targeting the resources’ metadata elements defined by the EDM Europeana model. All the data collected for this study from Europeana digital resources are the result of four explorations since 2012-2016.

The autors found that Europeana as a digital library has good levels of coverage of digital resources for those terms in the AAT thesaurus explored (terms from the “Styles and Periods” subset). This subset was selected as an example of faceted search given that it is a common search topic in the academic environment. However, it is important to remark the use of common vocabulary words provided by participants in order to obtain relevant results of search based on specific knowledge areas defined by AAT terms.

This research used a relatively small sample size of resources which may not be representative of the general size of Europeana digital resources. However, the results are illustrative as they are based on a specific knowledge area of AAT (118 terms) which contains very common topics used in high school courses by students and teachers in the field of art and cultural heritage. The study also aspires to provide a systematic method for conducting future studies in other knowledge areas.

The coverage study aims to analyze if Europeana is a digital library that teachers could use for the development of learning objects in specific knowledge areas, through the reuse of free/open access digital resources.

This study aims to let researchers sort out the past, look to the future and boost further management research.

This paper takes the exploration of the application of AR in the field of management research as the starting point. Through the combing and induction of AR literature to accurately grasp the essential characteristics of AR, this paper analyzes the application prospects and possible difficulties of AR in the field of management research in China, puts forward specific suggestions and explores the specific path of the transformation of management academic research to practice from the perspective of research methods.

In research methods, empirical research and case studies have become the mainstream research methods, but there is a passive research limitation of “study what happens.” Action research is different from the standpoint of empirical research that is independent of the research object. It no longer simply treats managers as the “object of information acquisition,” but as the subject of participating in the research. Management should be oriented towards the transformation of practice, and action research (AR) that can organically integrate researchers and practitioners is just a “bridge” to break the gap between academia and business circles to establish a cooperative relationship.

This paper takes the exploration of the application of AR in the field of management research as the starting point. Through the combing and induction of AR literature to accurately grasp the essential characteristics of AR, this paper analyzes the application prospects and possible difficulties of AR in the field of management research in China, puts forward specific suggestions and explores the specific path of the transformation of management academic research to practice from the perspective of research methods.

The purpose of this paper is to optimise the job shop scheduling problem using simulation and genetic algorithm.

The paper presents a simulation‐based genetic algorithm approach for the job shop scheduling problem. In total, three cases have been considered to access the performance of the job shop, with an objective to minimise mean tardiness and makespan. A restart scheme is embedded into regular genetic algorithm in order to avoid premature convergence.

Simulation‐based genetic algorithm can be used for job shop scheduling problems. Moreover, a restart scheme embedded into a regular genetic algorithm results in improvement in the fitness value. Single process plans selected on the basis of minimum production time criterion results in improved shop performance, as compared to single process plans selected randomly. Moreover, availability of multiple process plans during scheduling improves system performance measures.

The paper presents a simulation‐based genetic algorithm approach for job shop scheduling problem, with and without restart scheme. In this paper the effect of multiple process plans over single process plans, as well as criterion for selection of single process plans, are studied. The findings should be taken into account while designing scheduling systems for job shop environments.

This paper aims to focus on corporate social responsibility in relation to economic policy uncertainty in mergers and acquisitions (M&A). The following questions are addressed: How does policy uncertainty impact corporate M&A? Does social responsibility play a mediating role in this process? How does policy uncertainty affect corporate M&A through social responsibility?

This paper selects the major M&A events in China as the research object, and uses the Probit model to analyze the impact of policy uncertainty on M&A behavior and the business performance after the event, and further analyzes the internal mechanisms that cause these phenomena.

This paper shows that the higher the policy uncertainty, the lower the probability of a successful M&A, and the worse the business performance of the business after the event.

This paper provides useful reference for the study of M&A and social responsibility in different policy environments. At the same time, it provides direct empirical evidence to enhance the success rate of M&A.