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This paper aims to examine the conditions under which small and medium enterprises (SMEs) invest in security services when they migrate their e-commerce applications to the cloud environment. Using a risk management perspective, the paper assesses the impact of security service pricing, security incident prevalence and virulence to estimate SME security spending at the market level and draw out implications for SMEs and security service providers.

Security risks are inherently characterized by uncertainty. This study uses a Monte Carlo approach to understand the role of uncertainty in the decision to adopt security services. A model relating key security constructs is assembled based on key constructs from the domain. By manipulating security service costs and security incident types, the model estimates the market-level adoption of services, security incidents and damages incurred, along with measures of their relative dispersion.

Three key findings emerge from this study. First, adoption of services and protection is higher when tiered security services are provided, indicating that SMEs prefer to choose their security services rather than accept uniformly priced products. Second, SMEs are considered price-sensitive, resulting in a maximum level of spending in the market. Third, results indicate that security incidents and damages can be much higher than the mean in some cases, and this should serve as a cautionary note to SMEs.

Security spending has been modeled at the firm level. Adopting a market-level perspective represents a novel contribution. Additionally, the Monte Carlo approach provides managers with tangible measures of uncertainty, affording additional information and insight when making security service adoption decisions.

The study has a two-fold purpose: first, to identify the enablers of partnering agility in higher education, and, second, to analyze the interplay between the enablers.

Total interpretive structural modelling (TISM) was used to construct a theoretical model of partnering agility enablers, and cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to rank and segregate the enablers into independent, autonomous, dependent and linkage zones on the basis of their driving and dependence power.

The study helped in identifying eight enablers that can be instrumental in driving partnering agility in higher education. According to the TISM model, clarity on roles and responsibilities of partners was found to be the most crucial and vital enabler followed by resource sharing.

The conceptual model provides a new direction on how to develop and strengthen higher education partnerships. The model has prioritized all the crucial enablers that the management can work around in order to drive partnering agility in higher education institutions.

Studies in the past have majorly focused on academia–industry partnerships. This research has tried to provide a comprehensive view of the enablers and the multidirectional interplay between the enablers that can facilitate partnerships between academia and industry, Indian and international universities, and academia and community.

The purpose of this study is to explore the effect of reviewer qualification and credibility (RQC) and hotel classification involving online hotel reviews (OHRs). The study examines the effects of the reviewer level as a proxy of RQC on review helpfulness and reviewing behavior (review rating, review length). The study also included hotel classification as a moderating variable.

Data from 1,968 reviews were collected from TripAdvisor.com using a web data-harvesting technique. Hypothesized relations in the model were tested with t-test and MANOVA analysis.

The empirical results show that the effect of reviewer level on review helpfulness is not significant. In addition, a high-level reviewer tends to leave a lower rating and a lengthier review than a low-level reviewer. Regarding the moderating effects, for the high-level reviewer, three-star independent hotels have a greater effect on review helpfulness.

The study has several useful implications for researchers, hotel industry when managing OHR and disseminating information to their potential consumers.

The findings help online review website organizers manage the operation of RQC and hotel classification in a proper manner. Marketing managers, especially those of three-star independent hotels, can effectively utilize review management to the desired effect.

Unlike previous studies, this study explores the effect of RQC on review helpfulness and reviewing behaviors across the hotel classification. In addition, this study contributes to the hotel industry developing more effective online reviews from the reviewer level and diverse hotel types (three-star independent, four-star chain, five-star luxury hotels).

Based on self-determination theory (SDT), this study aims to determine the motivation factors of reviewers writing long reviews in the anime industry.

This study analyzes 171,188 online review data collected from an online anime community (MyAnimeList.net).

The findings show that intensity of emotions, experience in writing reviews and helpful votes in past reviews are the most important factors and positively influence review length. The overall rating of the anime moderates the effects of some motivation factors. Moreover, reviewers commenting on their favorite or nonfavorite anime also have varied motivation factors. Furthermore, this study has addressed the p-value problem due to the large sample size.

This study provides a comprehensive and theoretical understanding of reviewers' motivation for writing long reviews.

Online communities can incorporate the insights from this study into website design and motivate reviewers to write long reviews.

Many past studies have investigated what reviews are more helpful. Review length is the most important factor of review helpfulness and positively affects it. However, few studies have examined the determinants of review length. This study attempts to address this issue.

The purpose of this paper is to presents an analysis of geographically and disciplinary scattered academic publications of cloud computing (CC) research in information systems. This review aims to understand the research methodology, research frameworks and models, geographical distribution, trends, critical factors and causal relationships associated with cloud computing adoption (CCA).

Systematic-literature-review using natural language processing is conducted to explore the phenomenon. The relevant research studies are extracted from various online databases using quality-assessment-criteria.

The study is a novel attempt to highlight the differences in critical factors for CCA in different country-settings. Further, the research explores the causal relationships among the identified factors. The findings of this 12-year systematic-review contribute by aiding the providers and potential adopters to devise context-specific strategies for the penetration of cloud services and sound adoption decisions (ADs), respectively. The findings also highlight the prospective avenues of research in the domain for researchers. Using the in-depth analysis, conceptual frameworks have been proposed that can assist in exploring the pre-adoption and post-adoption of CC.

This study contributes to CCA research by providing holistic insights into the methodology, research framework and models, geographical focus, critical factors and causal relationships influencing the AD or intention. The review highlights the unexplored emerging research topics in the field of CCA for future research directions.

As retailers have increasingly embraced an omnichannel retailing strategy, explaining and predicting the helpfulness of online review should consider both online-based and offline-based reviews. The paper aims to discuss this issue.

Based on the signaling theory, this study intends to examine the impacts of review-related and reviewer-related signals on review helpfulness in the context of omnichannel retailing. The proposed research model and corresponding hypotheses were tested by using negative binomial regression.

The results shown that both review-related (review rating and review sentiment strength) and reviewer-related (reviewer real name and reviewer expertise) signals positively affect review helpfulness. Contrary to the authors’ expectations, review length negatively affects review helpfulness. Specifically, when the review submitted from an omnichannel retailer’s offline channel, the positive impacts of reviewer real name on review helpfulness will be stronger, and the positive impacts of reviewer expertise on review helpfulness will be weaker.

Unlike many previous studies tend to explore the antecedents of review helpfulness in a single-channel setting, the study examined the factors that affect review helpfulness in an omnichannel retailing context.

This study aims to develop a scale to measure the cloud provider’s performance and it investigates the factors that impact that performance from the users’ perspective.

This paper proposes a research framework, develops hypotheses and conducts a survey to test the framework.

The results from both ordinary least square regression and structural equation modeling analyzes indicate that information technology complexity negatively and significantly affects users’ perception of the cloud computing providers’ performance. Additionally, the trust in the supervisor significantly enhances the otherwise insignificant positive relationship between providers’ cybersecurity capability and users’ perception of their providers’ performance.

The research makes important contributions to the cloud computing literature, as it measures users’ perception of the cloud computing provider’s performance and links it with cybersecurity, technical complexity and incorporates both the trust in the client firm’s supervisor and the strength of cybersecurity offered by cloud computing provider.

This study aims to explain the implementation of Cloud enterprise resource planning (ERP) system and underlying factors and challenges that might be practiced by the users. It also provides a comparison between traditional and Cloud ERP systems.

The study uses qualitative case study and analyzes the primary evidences from in-depth interviews. It conducts a thematic analysis of the interviews' findings. Furthermore, the current study uses three groups of factors (technological, management and environmental) that are expected to be best determinants of the Cloud ERP implementation.

The findings provide an evidence that using the Cloud EPR system, as alternative to on premise traditional ERP system, is constructive to the success of organizations and improve the quality of their decision-making process. The findings also reveal that effectiveness of implementing Cloud ERP is reliable on the provider's professionalism; hence resulting in issues related to minimize organizational independence.

This paper is subjected to case studies limitations, as it lacks rigor and generalization. The paper has important implications for practitioners and decision-makers alike as it presents real-life example about Cloud ERP implementation. It thus enhances decision-makers' ability to make a relevant reporting process in the small and medium enterprises (SMEs).

This study can be considered as a one of very few case studies that discusses Cloud ERP implementation in UAE organizations particularly SMEs. It also provides three groups of factors (technological, management and environmental) that are influenced by the Cloud ERP implementation.