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This paper aims to examine the influences of the number of hotel management responses and especially the textual similarity in hotel management responses to online reviews on hotel online booking.

This study used the data from 437 hotels in New York City on Expedia. The data specifically include online reviews, management responses and real-time number of online hotel bookings, which were merged to create one dataset for this study. To calculate the management response similarity, three widely recognized text mining functions of calculating textual similarity were adopted in this model. Fixed-effect panel data model was then used to examine the influence of management response to consumer online reviews on online hotel booking volume.

The empirical results demonstrate that the number of management responses to consumer online reviews does not significantly affect hotel booking; compared to none or only one management response, or management responses with low similarity, management responses with high similarity can significantly reduce the hotel booking on Expedia.

This study suggests that the similarity of management responses influences customers’ hotel booking, and hotel managers should avoid providing too similar management responses.

First, this study, for the first time, proposes the concept of management response similarity and its measurement methods. Second, this study takes an initial attempt to empirically test the influence of response similarity on hotel booking by using secondary data online.

The purpose of this paper is to investigate the effect of perceived product similarity and comparative ad claims on brand responses.

This study uses a two (similarity between the target product and the comparison product: relatively similar vs dissimilar) by three (product attributes of the target product: common to the comparison product, distinct from the comparison product, and a combination of common and distinct attributes) between-subjects factorial design with 300 Thai undergraduate students.

It finds that when perceived similarity between the products is high, a combination of superiority (distinct) and parity (common) ad claims lead to the best brand responses. When perceived similarity is low, superiority claims bring about the best brand responses.

It extends comparative advertising and category-substitution research by addressing the research gaps in perceived similarity and claim type.

Companies should emphasize a product’s superior attributes in general but a combination of common and superior attributes when the product is relatively similar to other products in comparative advertising.

This study provides new evidence that perceived product similarity moderates the effect of comparative ad claims on brand responses.

Adopting the theory of parasocial interaction (PSI) and schema theory, this study proposes that a brand’s personalized response and brand familiarity on a corporate blog will lead to higher perceived brand similarity, credibility and blog recommendation intention.

A 2 (brand familiarity: high, low) × 3 (brand responses: none, automated and personal) experimental design was developed to test the hypothesized relationships. A total of 474 qualified data were collected using an online survey. ANOVA was utilized to test the research hypotheses.

Study results revealed that personalized messages lead to stronger perceived brand similarity, credibility and blog recommendation intention than those exposed to automated and no response. Brand familiarity also significantly influenced perceived brand similarity, brand credibility and blog recommendation intention. Further, the study analysis revealed an interesting interaction effect between brand awareness and brand response on recommendation intention.

The study provides meaningful implications and suggestions for the effective corporate blogging strategy to influence consumers’ attitudes and image toward brands and establish strong brand equity and relationships with customers.

This paper aims to quantify the quality of peer reviews, evaluate them from different perspectives and develop a model to predict the review quality. In addition, this paper investigates effective features to distinguish the reviews' quality. 

First, a fine-grained data set including peer review data, citations and review conformity scores was constructed. Second, metrics were proposed to evaluate the quality of peer reviews from three aspects. Third, five categories of features were proposed in terms of reviews, submissions and responses using natural language processing (NLP) techniques. Finally, different machine learning models were applied to predict the review quality, and feature analysis was performed to understand effective features.

The analysis results revealed that reviewers become more conservative and the review quality becomes worse over time in terms of these indicators. Among the three models, random forest model achieves the best performance on all three tasks. Sentiment polarity, review length, response length and readability are important factors that distinguish peer reviews’ quality, which can help meta-reviewers value more worthy reviews when making final decisions.

This study provides a new perspective for assessing review quality. Another originality of the research lies in the proposal of a novelty task that predict review quality. To address this task, a novel model was proposed which incorporated various of feature sets, thereby deepening the understanding of peer reviews.

The aim of the research presented here was to identify behavioural cues of rapport and warmth, in order to enable the construction of a valid measurement tool that would support existing methods of behavioural analysis. A number of general research questions were put to six focus groups. Participants were individuals with learning disabilities, professionals working for the NHS or a local authority, and support workers. Data obtained was qualitative in nature and was examined using content analysis and comparisons between participants' experiences. Methods of interaction and communication with people who were either liked or disliked were generally similar across groups, although this varied by specific category. Behavioural cues of rapport were identified and categorised. Most of these would be of use in the creation of an assessment tool, although some adjustment is required so that they can be measured. Implications of the findings are discussed.

University students often view economics as one of the most challenging subjects. In this paper, we explore whether the same attitude is shared by students at an offshore campus. The analysis is based on a survey of onshore and offshore students in an Australian university. The focus of the paper is on identifying similarities/differences in student attitudes towards economics, their degree of motivation, satisfaction with the content and the delivery of lectures and tutorials, major challenges, and student profile characteristics. A non‐parametric test indicates significant differences between the two cohorts, in terms of their age, enrolment status, paid work commitments, prior study of economics, their motivation and approach to studying the subject, and satisfaction with both the content and the delivery of the lectures/tutorials. The findings in this study are helpful in developing strategies for enhancing student learning in culturally diverse cohorts.

This study uses metaphor analysis to examine doctoral students’ conceptions obtained from their responses to an on‐line survey. The conceptions examined were the conception of self in research, the conception of the PhD, the conception of knowledge, and the conception of the outcomes of research. The conceptions found were allocated to the categories of “organic”, “spatial”, “explorative” and “constructive”, the same categories as were used in a previous study of the students’ conceptions of research. A number of interesting relationships were found and are discussed, including the relationship of the conceptions to each other and to the demographic data obtained in the survey. Some tentative conclusions are discussed and some speculation indulged in. Since the supervisor/student relationship may be affected by any mis‐match between their conceptions, that mis‐match, if present, will also affect the student’s progress and development.

The purpose of this study is to evaluate the effect of both positive and negative corporate cultures on employee performance in Saudi Arabia, in the presence of performance reviews and factors leading to positive work culture, in an environment that underwent serious modification with COVID-19. The changing work methods (online, remote, etc.) have left their mark necessitating revisiting the needs and capabilities of employees in the work environment.

This quantitative study uses primary data from small and medium-sized enterprises (SMEs), non-profit organizations, and transnational organizations, in their transient role and influence on organizational culture change. The data set includes 311 usable responses from 50 randomly selected organizations and is analysed using structural equation modelling to test the proposed model.

A healthy corporate culture serves as the basis for increased employee performance in the workplace. The three independent variables, availability of negative culture, availability of positive culture and employee perceived performance, have a positive impact on the dependent variable employee perceived effectiveness of performance reviews; however, factors leading to the development of a positive organizational has a negative influence.

This study faced a limitation with the potential similarity of responses due to the large number of same-background respondents (engineers). However, the results are indicative of a trend. Moreover, the responses did not allow for cross comparison between responding organizational types (SMEs, non-governmental organizations and multinational corporations) as was planned.

Managers should motivate their respective employees, through ensuring the diffusion and sustainability of the right culture work environment. This should allow their teams to complete tasks with little or no supervision. Moreover, as the Saudi economy is gearing up for global competitiveness, this performance culture becomes a key for the success of the strategic plans, thus the high importance of the positive culture at work today.

Understanding the importance of positive and negative culture at the managerial level would affect the relationship with employees and improve work environment and job satisfaction.

This study pinpoints the need to revisit a dimming topic, proving that with the end of the COVID-19 pandemic, managers need to go back to square one. The introduction of the many novel work systems, online, remote work, etc. have changed the work setting and environment. This is requiring a new look at the employees’ perceptions on factors influencing corporate culture and performance.

The development within storage and processing technologies combined with the growing collection of data has created opportunities for companies to create value through the application of big data. The purpose of this paper is to focus on how small and medium-sized companies in Denmark are using big data to create value.

The research is based on a literature review and on data collected from 457 Danish companies through an online survey. The paper looks at big data from the perspective of SMEs in order to answer the following research question: to what extent does the application of big data create value for small and medium-sized companies.

The findings show clear links between the application of big data and value creation. The analysis also shows that the value created through big data does not arise from data or technology alone but is dependent on the organizational context and managerial action. A holistic perspective on big data is advocated, not only focusing on the capture, storage, and analysis of data, but also leadership through goal setting and alignment of business strategies and goals, IT capabilities, and analytical skills. Managers are advised to communicate the business value of big data, adapt business processes to data-driven business opportunities, and in general act on the basis of data.

The paper provides researchers and practitioners with empirically based insights into how the application of big data creates value for SMEs.

Purpose – This chapter introduces two empirical models that could be used to examine the influence of Eastern and Western culture on strategic management: the cultural consensus model (CCM) and the cultural mixture model (CMM).

Methodology/approach – We describe how strategic management scholars can use these models and suggest areas where these models can be of greatest use, including international market entry, international mergers and acquisitions and international alliances, global headquarters and subsidiary relationships, and corporate governance.

Findings – Originally developed by cognitive anthropologists and cultural psychologists, these models can measure domain specificity, scope, and heterogeneity of cultural influences within and across Eastern and Western societies; can address multilevel issues; and can measure an individual or firm's representativeness of the culture.

Social implications – This new research methodology can help strategic management researchers address the impact of “West meets East” on strategic management outcomes and processes.

Originality/value of chapter – The two empirical models provide methodologies that integrate qualitative and quantitative methods.