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This study aims to provide a holistic review of social media influencers (SMIs) research based on a unique approach of bibliometric analysis and content analysis between 2011 and 2020. The review examines the main influential aspects, themes and research streams to identify research directions for the future.

The sample selection and data collection were done from the Scopus database. The sample dataset was refined based on the inclusion and exclusion criteria to determine the final dataset of 183 articles. The dataset was exported in the BibTeX format and then imported into the BiblioShiny app for bibliometric analysis. The content analysis was done following the theory-context-methodology framework.

The several findings of this study include (1) Co-word analysis of most used keywords; (2) Longitudinal thematic evolution; (3) The focus of the research papers as per the theory-context-methodology review protocol are persuasion knowledge model, fashion and beauty industries, Instagram and content analysis, respectively; and (4) The network analysis of the research studies is known as the co-citation analysis and depicts the intellectual structure in the domain. This analysis resulted in four clusters of the research streams from the literature and two emergent themes (Chen et al., 2010)

In general, the previous reviews in the area are either domain, method or theory-based. Thus, this study aims to complement and extend the existing literature by presenting the overall picture of the SMI research with the help of a unique combined approach and further highlighting the trends and future research directions based on the findings of this study.

This paper evaluates the precision of four metasearch engines (MSEs) – DuckDuckGo, Dogpile, Metacrawler and Startpage, to determine which metasearch engine exhibits the highest level of precision and to identify the metasearch engine that is most likely to return the most relevant search results.

The research is divided into two parts: the first phase involves four queries categorized into two segments (4-Q-2-S), while the second phase includes six queries divided into three segments (6-Q-3-S). These queries vary in complexity, falling into three types: simple, phrase and complex. The precision, average precision and the presence of duplicates across all the evaluated metasearch engines are determined.

The study clearly demonstrated that Startpage returned the most relevant results and achieved the highest precision (0.98) among the four MSEs. Conversely, DuckDuckGo exhibited consistent performance across both phases of the study.

The study only evaluated four metasearch engines, which may not be representative of all available metasearch engines. Additionally, a limited number of queries were used, which may not be sufficient to generalize the findings to all types of queries.

The findings of this study can be valuable for accreditation agencies in managing duplicates, improving their search capabilities and obtaining more relevant and precise results. These findings can also assist users in selecting the best metasearch engine based on precision rather than interface.

The study is the first of its kind which evaluates the four metasearch engines. No similar study has been conducted in the past to measure the performance of metasearch engines.

Variations in customer expectations pose a challenge to service quality improvement in the airline industry. Understanding airline customers' expectations and satisfaction help service providers improve their offerings. The extant literature examines airline passengers' expectations in isolation, neglecting the overall impact of online reviews on service quality improvement. This paper systematically evaluates the airline industry's passengers' expectations and satisfaction using expectation confirmation theory (ECT) and the SERVQUAL framework. The paper analyzes online reviews to examine the relationship between airline service quality attributes and passengers' satisfaction.

The SERVQUAL framework was employed to examine the effects of customer culture, the reason for traveling, and seat type on customer's expectations and satisfaction across a large sample of airline customers.

A total of 17,726 observations were gathered from the Skytrax review website. The lowest satisfaction ratings were from passengers from the USA, Canada and India. Factors that affect perceived service performance include customer service, delays and baggage management. Empathy and reliability have the biggest impact on the perceived satisfaction of passengers.

This research increases understanding of the consumer expectations through analysis of passengers' online reviews. Results are limited to a small sample of airline industries.

This study provides airlines with valuable information to improve customer service by analyzing online reviews.

This study provides the opportunity for airline customers to gain better services when airline companies utilize the findings.

This paper offers insights into passengers' expectations and their perceived value for money in relation to seat types. Previous studies have not investigated value for money as a construct for passengers' expectations and satisfaction relative to service quality dimensions. This paper addresses this need.

This study develops a measure of anticipated chilly climate for women and provides initial evidence of its validity.

We draw on three studies. Study 1 consisted of three focus groups to gain deeper insights into the meaning of the concept for prospective female jobseekers and generate scale items. In Study 2, we pre-tested job post vignettes (N = 203), refined the scale items and explored the factor structure (N = 136). Study 3 aimed to determine the convergent and discriminant validity of the new scale (N = 224) by testing its relationships with organisational attractiveness, person-organisation fit perceptions and gendered language.

The results show that the anticipated chilly climate is an important concept with implications for applicants’ career decision-making and career growth in the technology industry, where women tend to be underrepresented. Perceptions of anticipated chilly climate comprise expectations of devaluation, marginalisation and exclusion from the prospective employment. The masculine stereotypes embedded in the language of the job posts signalled a chilly climate for both genders, negatively affecting perceptions of fit and organisational attractiveness.

Most previous studies have focussed on the actual experiences of chilly climates in organisations. We extend this body of literature to anticipatory climates and draw on social identity threat theory and signalling theory to highlight that job applicants make inferences about the climate they expect to find based on job ads. Specifically, they may anticipate a chilly climate based on cues from job ads signalling masculine stereotypes. Whilst the literature has emphasised women’s perceptions of chilly climates within organisations, our results show that both genders anticipate chilly climates with detrimental consequences for both organisations and prospective job applications.

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging behind other disciplines. This paper aims to provide a review of the current use of data analytics in project delivery encompassing both academic research and practice to accelerate current understanding and use this to formulate questions and goals for future research.

We propose to achieve the research aim through the creation of a systematic review of the status of data analytics in project delivery. Fusing the methodology of integrative literature review with a recently established practice to include both white and grey literature amounts to an approach tailored to the state of the domain. It serves to delineate a research agenda informed by current developments in both academic research and industrial practice.

The literature review reveals a dearth of work in both academic research and practice relating to data analytics in project delivery and characterises this situation as having “more gap than knowledge.” Some work does exist in the application of machine learning to predicting project delivery though this is restricted to disparate, single context studies that do not reach extendible findings on algorithm selection or key predictive characteristics. Grey literature addresses the potential benefits of data analytics in project delivery but in a manner reliant on “thought-experiments” and devoid of empirical examples.

Based on the review we articulate a research agenda to create knowledge fundamental to the effective use of data analytics in project delivery. This is structured around the functional framework devised by this investigation and highlights both organisational and data analytic challenges. Specifically, we express this structure in the form of an “onion-skin” model for conceptual structuring of data analytics in projects. We conclude with a discussion about if and how today’s project studies research community can respond to the totality of these challenges. This paper provides a blueprint for a bridge connecting data analytics and project management.

This study aims to contribute to the field of customer portfolio management by proposing a novel approach rooted in dialectic critical realism (DCR). DCR, as an ontological theory, enables a fundamental reimagining of customer portfolio management as a dialectic process. The conceptualized dialectic portfolio management is motivated by the concept of “absence”, akin to Hegelian “antithesis”, which highlights limitations, problems and tensions in portfolio management. In essence, “absence” serves as a diagnostic tool that directs portfolio actions towards resolving problems by pursuing a more comprehensive “totality”, similar to the Hegelian notion of “synthesis”.

This conceptual paper theorizes DCR in business marketing and customer portfolio management.

DCR conceptualizes customer portfolios as relational structures characterized by omissions and tensions. These issues are addressed through a dialectic synthesis aimed at achieving a more comprehensive “totality”. Consequently, DCR guides portfolio management to continually re-think the connections and distinctions that define a portfolio within its network context. This dialectic process is facilitated by a novel vocabulary that enhances the understanding of network and portfolio relations, incorporating concepts such as “intrapermeations”, “existential constitutions”, “intra-connections” and “intensive” and “extensive” portfolio practices.

This study aims to foster a fresh and process-oriented perspective on portfolio management, drawing inspiration from the growing demand for enriched dialectic theorizing within the realm of business marketing. The adoption of a dialectic process orientation based on DCR revolutionizes the comprehension of portfolio management by fundamentally reimagining the underlying ontological assumptions that underpin the existing body of literature on customer portfolios. Moreover, DCR asserts that ethical considerations are inextricably linked to human experiences and associated practices, emphasizing ethics as an integral component of customer portfolio management.

This study proposes and validates an integrated theoretical model involving the theory of planned behavior (TPB), health belief model (HBM), personal norms and information privacy to understand determinants of acceptance and resistance to the use of mobile contact tracing app (MCTA) in a pandemic situation.

This study draws on online surveys of 194 research respondents and uses partial least squares structural equation modeling (PL-SEM) to test the proposed theoretical model.

The study establishes that a positive attitude towards MCTA is the most important predictor of individuals' willingness to use MCTA and resistance to use MCTA. Furthermore, barriers to taking action positively influence resistance to the use of MCTA. Personal norms negatively influence resistance to the use of MCTA. Information privacy showed a negative and positive influence on willingness to use MCTA and use the resistance of MCTA, respectively, but neither was statistically significant. The authors found no significant influence of perceived vulnerability, severity, subjective norms and perceived behavioral control on either acceptance or use resistance of MCTA.

The study has been one of the first in the literature to propose an integrated theoretical model in the investigation of the determinants of acceptance and resistance to the use of MCTA in a single study, thereby increasing the scientific understanding of the factors that can facilitate or inhibit individuals from engaging in the use of a protection technology during a pandemic situation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0533

This study aims to explore the conversion of metaverse marketing (MVM) into strategic agility among SMEs based on dynamic capabilities (DC) and dynamic management capabilities (DMC) theories. This paper discusses how constructs such as immersive marketing technologies (IMT), customer immersion (CI) and managerial capabilities (MC) play critical role in the transformation of MVM into strategic agility (SA).

A theoretical framework based on DC and DMC theories, and a comprehensive review of the literature on MVM, IMT, CI, MC and SA, was developed in order to theoretically investigate the relationships between MVM and SA. In this theoretical framework, MVM is the independent variable, while the dependent variable is SA. Also, IMT and CI both mediate the association between MVM and SA, while MC moderate the association between MVM and SA in one stream; and CI and SA in another stream.

This research study develops a theoretical framework that recommends nine set of important research propositions in MVM. An extensive literature review was conducted to examine the theoretical framework on the effect of MVM on SA. The proposed theoretical framework suggests that brand community development and communication, experiential marketing and personalisation in MVM, once accessed through IMT (i.e. VR, AR, MR) and CI (i.e. customer engagement, customer absorption-customer acquisition and assimilation of knowledge, presence) can produce significant SA through customer experience management, value co-creation and process innovation.

This current study develops a theoretical framework that theorise the relationship between MVM and SA rooted in literature on MVM and SA, and also based on DC and DMC perspective. The moderating effect of MC on the relationship between IMT and SA on one hand, and CI and SA on the other, provides support to IMT and CI as mediators in the transformation of MVM into SA. This study also provides insight into SME adoption of MVM and how it generates SA. Lastly, the current study contributes to the body of knowledge on MVM, IMT, CI, MC and SA.