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This study aims to examine the factors influencing trust toward mobile health applications (mhealth apps) among young consumers. By building on the socio-technical systems framework and self-congruence theory, the authors develop and examine a conceptual model of the trusting intentions of young consumers toward mhealth apps.

The data for the study was collected from a sample of 285 young consumers via an online survey by using a purposive sampling method. All the respondents were existing users of health apps and resided in the urban areas of the country. The sample comprised 53% male respondents and 47% female respondents. Subsequently, the data was analyzed using the structural equation modeling technique.

The findings revealed that psychological factors like self-congruence and technical factors such as flow experience and perceived playfulness aid in building trust among young mhealth app users, which in turn influences the purchase intention and user loyalty toward the application. Social factors like perceived critical mass and social influence did not significantly impact trust.

The data was collected from Generation Z, recognized as the most influential consumer demographic worldwide, primarily involved in mhealth app usage. Nonetheless, it is essential to understand that these findings might only partially apply to a specific user group. In addition, the study did not focus on any specific mhealth applications. Hence, it is prudent to exercise caution when generalizing these results to the broader population.

This study advances the comprehension of socio-technical elements in establishing trust, subsequently impacting purchase intentions and loyalty among young users in the context of mhealth apps. In addition, it expands the socio-technical framework by incorporating a psychological factor that could influence trust and purchase intentions toward mhealth apps. Furthermore, the post hoc findings reinforce this comprehension by identifying the moderating effects of operating system type and gender. These insights could provide valuable guidance for developing tailored marketing strategies targeting the young consumer base.

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.

We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.

Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.

This is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.

In today’s rapidly evolving business landscape, innovation is the cornerstone for every organization. Knowledge management (KM) is crucial for developing sustainable competitive advantage by fostering innovation. This study aims to identify the key drivers of KM in the context of digital transformation through qualitative research.

This study employs a qualitative approach based on in-depth interviews with senior KM officers, including chief knowledge officers and directors who spearhead KM in their respective organizations. This research identifies four key dimensions, shedding new light on the drivers of KM in the context of digital transformation.

This study’s findings reveal that the integration of important drivers from the lens of social-technical system (STS) theory is categorized into the four dimensions of KM, namely, motivation, technology, people interaction and organizational drivers. These factors jointly impact and design the effectiveness of KM in the digital age.

This study makes a unique contribution to the field of digital transformation. It presents a conceptual framework from the lens of the STS theory that encompasses four critical dimensions of KM: motivation, technology, people interaction and organizational dimensions, each with sub-codes. This framework can be utilized by practitioners and scholars alike.

Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

The purpose of this paper is to emphasize the needs to understand the barrier and determinant factors in knowledge sharing (KS), to find the common ones and subsequently to build a general framework that can be referred to in designing a KS tool that addresses the common factors.

The approach comprises of two major steps which are to survey the past literature to determine the most common barriers and determinant factors from various unique KS domains and to qualify the factor as the common one based on its presence in at least three to five KS domains. The grounded theory is used to analyze the past literature and to perform categorization.

This paper helps in the summarization of categories and subcategories of barriers and determinants and demonstration on the mapping between them.

This paper has not proved the actual use of the framework in building a KS tool based on the framework.

The common factors are based on at least 60 references of KS implementation such that it is useful for large area of application domains that require building KS tools.

This paper presents the understanding on the common factors and association between the barriers and determinants in building the general framework in which the application of the framework is demonstrated using actor network theory.

The aim of this study is to investigate how the demographics and appearance cues of potential social engineers influence the likelihood that targets will trust them and accept security risk.

Data were collected through an online survey of 635 participants, including 322 participants from Arab countries and 313 participants from the UK. The survey presented scenarios with 16 personas who offered participants the use of their mobile internet hotspot. These personas were characterized by combinations of age (young vs aged), gender (male vs female), ethnicity (Arab vs UK) and look formality (casual vs formal). The study measured both participants’ offer acceptance and trust in the persona.

Results indicated a higher likelihood of offer acceptance from female and aged personas, as well as a greater trust in these groups. Arab participants showed a preference for personas with Arabian ethnic features. In both samples, trust and acceptance were influenced by the persona’s appearance, which was found to be gender-dependent; with female personas in casual attire and male personas in formal attire being trusted more in comparison to female with formal attire and male with informal, respectively.

Findings highlight the importance of incorporating awareness of appearance-based biases in cybersecurity training, suggesting the need for culturally sensitive training programs to enhance defense against social engineering.

This study distinguishes itself by elucidating the influence of social engineers’ demographic and appearance cues on the likelihood of individuals to take security risks, thus addressing a significant gap in the literature which has traditionally emphasized the profiles of targets.

High-stakes decision-makers, including human resource (HR) professionals, often exhibit accent biases against second language speakers in professional evaluations. We extend this work by investigating how HR students evaluate simulated job interview performances in English by first and second language speakers of English.

Eighty HR students from Calgary and Montreal evaluated the employability of first language (L1) Arabic, English, and Tagalog candidates applying for two positions (nurse, teacher) at four points in the interview (after reading the applicant’s resume, hearing their self-introduction, and listening to each of two responses to interview questions). Candidates’ responses additionally varied in the extent to which they meaningfully answered the interview questions.

Students from both cities provided similar evaluations, employability ratings were similar for both advertised positions, and high-quality responses elicited consistently high ratings while evaluations for low-quality responses declined over time. All speakers were evaluated similarly based on their resumes and self-introductions, regardless of their language background. However, evaluations diverged for interview responses, where L1 Arabic and Tagalog speakers were considered more employable than L1 English speakers. Importantly, students’ preference for L1 Arabic and Tagalog candidates over L1 English candidates was magnified when those candidates provided low-quality interview responses.

Results suggest that even in the absence of dedicated equity, diversity, and inclusion (EDI) training focusing on language and accent bias, HR students may be aware of second language speakers’ potential disadvantages in the workplace, rewarding them in the current evaluations. Findings also highlight the potential influence of contextual factors on HR students’ decision-making.

This paper aims to provide insights into the environment needed for advancing a digitally enabled circular plastic economy in Africa. It explores important technical and social paradigms for the transition.

This study adopted an interpretivist paradigm, drawing on thematic analysis on qualitative data from an inter-sectoral engagement with 69 circular economy stakeholders across the continent.

The results shows that, while substantial progress has been made with regard to the development and deployment of niche innovations in Africa, the overall progress of circular plastic economy is slowed due to relatively minimal changes at the regime levels as well as pressures from the exogenous landscape. The study highlights that regime changes are crucial for disrupting the entrenched linear plastic economy in developing countries, which is supported by significant sunk investment and corporate state capture.

The main limitation of this study is with the sample as it uses data collected from five countries. Therefore, while it offers a panoramic view of multi-level synergy of actors and sectors across African countries, it is limited in its scope and ability to illuminate country-specific nuances and peculiarities.

The study underlines the importance of policy innovations and regulatory changes in order for technologies to have a meaningful contribution to the transition to a circular plastic economy.

The study makes an important theoretical contribution by using empirical evidence from various African regions to articulate the critical importance of the regime dimension in accelerating the circular economy transition in general, and the circular plastic economy in particular, in Africa.

The COVID-19 pandemic necessitated a significant shift in how employees executed their professional responsibilities. Concurrently, the incidence of cybercrime experienced a noteworthy surge due to the increased utilisation of cyberspace. The abrupt transition to telecommuting altered the interpersonal dynamics inherent in traditional work environments. This paper aims to examine the impact of interpersonal factors on the cybercrime preventative measures adopted by telecommuting employees.

A conceptual model, grounded in the Theory of Interpersonal Behaviour, is evaluated through an online survey. The data set comprises responses from 209 employees in South Africa, and the analysis uses partial least squares structural equation modelling.

The results reveal substantial predictive power to explain cybercrime preventative behaviours. Notably, the study underscores the significant influence of habit and affect on intention and subsequent behaviour.

The results suggest that practitioners should give due attention to emotional dimensions (affect) as a catalyst for information security behaviour. The formulation of employees’ information security responsibilities should be pragmatic, fostering subconscious compliance to establish routine behaviour (habit).

This research underscores the pivotal roles played by habit and emotions in shaping behavioural patterns related to information security. Furthermore, it provides researchers with an illustrative model for operationalising these constructs within the realm of security. The results contribute additional perspectives on the repercussions of the COVID-19 pandemic on cybercrime preventative behaviours.

Intellectual property (IP) theft is an increasing threat that can lead to large financial losses and reputational harm. These attacks are typically noticed only after the IP is stolen, which is usually too late. This paper aims to investigate the psychological profile and the socio-technical events that statistically predict the likelihood of an IP threat.

This paper analyses 86 IP theft cases found in court documents. Two novel analyses are conducted. The research uses LLMs to analyse the personality of these insiders, which is followed by an investigation of the pathways to the attack using behaviour sequence analysis (BSA).

These IP theft insiders scored significantly higher on measures of Machiavellianism compared to the normal population. Socio-technical variables, including IP theft via photographs, travelling overseas, approaching multiple organisations and delivering presentations, were identified. Contrary to previous assumptions that there is a single pathway to an attack, the authors found that multiple, complex pathways lead to an attack (sometimes multiple attacks). This work, therefore, provides a new framework for considering critical pathways to insider attacks.

These findings reveal that IP theft insiders may come across as charming, star employees rather than the stereotype of disgruntled employees. Moreover, organisations’ policies may need to consider that IP theft occurs via non-linear and multiple pathways. This means that sequences of events need to be considered in detecting these attacks instead of anomalies outright. The authors also argue that there may be a case for “continuous evaluation” to detect insider activity.

This paper offers a new framework for understanding and studying insider threats. Instead of a single critical pathway, this work demonstrates the need to consider multiple interconnected pathways. It elucidates the importance of a multidisciplinary approach and provides opportunities to reconsider current practices in detection and prevention.