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Digital platforms increase their function and scope by leveraging boundary resources and complementary add-on products from third-party developers to interact with external entities and producers. Application Programming Interfaces (APIs) are essential boundary resources developers use to connect applications, systems and platforms. This notwithstanding, previous API studies tend to focus more on the technical dimensions, with little on the social and cultural contexts underpinning API innovations. This study relies on the new (neo) institutional theory (focusing on regulative, normative and cultural-cognitive pillars) as an analytical lens to understand the institutional forces that affect API integration among digital firms.

The study adopts a qualitative case study methodology and relies on phone calls and a semi-structured in-depth interview approach of a Ghanaian digital music platform to uncover the institutional forces affecting API integration.

The findings reveal that regulative institutions such as excessive tax regimes mostly constrained API development and integration initiatives. However, other regulative institutions like the government digitalization agenda enabled API integration. Normative institutions, such as the growing use of e-payment options, enabled API integration in digital music platforms. Cultural-cognitive institutions like employee ego constrained the API integration process in music digital platforms.

This study primarily contributes to deepening understanding of the relevant literature by exploring the institutional forces that affect API integration among digital firms in a developing economy. The study also uncovered a new form of an institution known as motivational institution as an enabler for API development and integration in digital music platforms.

By providing a practical and theoretical framework on the role of digitalization in business model innovation (BMI) and countermeasures liabilities of foreignness (LoF), we aim to provide small and medium-sized enterprises (SMEs) from emerging markets with the means to confront the reality of de-internationalization.

A quantitative design emphasizing mature theory design and collecting survey data from 210 SMEs in an emerging market. The data are analyzed using a confirmatory factor analysis (CFA) based on covariance-based SEM (CB-SEM), multiple regression analysis (MRA) and Hayes' process model.

Digitalization was revealed to significantly and indirectly negatively affect SMEs’ de-internationalization via BMI. Besides, the conditional indirect effect of digitalization on de-internationalization through BMI is more robust and exists at the high LoF of SMEs.

We advise SMEs with a distinctive and relatively comprehensive strategy for coping with the pressures of de-internationalization or having their internationalization schedules perpetually altered through the lens of the resource-based view and institution theory.

This study explores the shopping orientations of omnichannel customers through the lens of generational cohort theory, which influences their decision-making style while shopping online. It offers key insights into how Generations X, Y and Z interact with digital platforms, helping retailers adapt to the shifting dynamics of modern customers.

Using different customer decision-making styles, a comprehensive questionnaire was administered to a diverse sample selected via systematic probability sampling. The responses were analysed using multivariate and post hoc analysis to uncover generational and product-based differences in online shopping orientations.

The analysis reveals apparent generational differences. Gen Z is driven by affordability and quality, while Gen Y is brand-conscious and willing to pay premium prices. In contrast, Gen X exhibits strong brand loyalty, although younger generations show a decline in brand attachment. These findings suggest that retailers must blend online and offline channels to boost customer engagement and loyalty, especially among omnichannel customers.

The study relies on self-reported data, introducing the potential for recall bias, which could affect the accuracy of reported behaviours.

Understanding different generational cohorts’ distinct online shopping behaviours empowers marketers and retailers to craft personalised strategies that enhance customer engagement and drive brand loyalty and satisfaction. By tailoring experiences to the unique preferences of each generation, retailers can ensure seamless shopping journeys that resonate across product categories, maximising their market impact and customer retention.

By applying generational cohort theory, this study uniquely examines the underexplored group of omnichannel customers, offering fresh insights through multivariate analysis into how generational cohorts and product types shape online shopping behaviour, providing valuable guidance for retailers.

The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG), electromyography (EMG), electrodermal activity (EDA), temperature, plethysmograph and respiration. The experiments are conducted on both modalities independently and in combination. This study arranges the physiological signals in order based on the prediction accuracy obtained on test data using time and frequency domain features.

DEAP dataset is used in this experiment. Time and frequency domain features of EEG and physiological signals are extracted, followed by correlation-based feature selection. Classifiers namely – Naïve Bayes, logistic regression, linear discriminant analysis, quadratic discriminant analysis, logit boost and stacking are trained on the selected features. Based on the performance of the classifiers on the test set, the best modality for each dimension of emotion is identified.

 The experimental results with EEG as one modality and all physiological signals as another modality indicate that EEG signals are better at arousal prediction compared to physiological signals by 7.18%, while physiological signals are better at valence prediction compared to EEG signals by 3.51%. The valence prediction accuracy of EOG is superior to zygomaticus electromyography (zEMG) and EDA by 1.75% at the cost of higher number of electrodes. This paper concludes that valence can be measured from the eyes (EOG) while arousal can be measured from the changes in blood volume (plethysmograph). The sorted order of physiological signals based on arousal prediction accuracy is plethysmograph, EOG (hEOG + vEOG), vEOG, hEOG, zEMG, tEMG, temperature, EMG (tEMG + zEMG), respiration, EDA, while based on valence prediction accuracy the sorted order is EOG (hEOG + vEOG), EDA, zEMG, hEOG, respiration, tEMG, vEOG, EMG (tEMG + zEMG), temperature and plethysmograph.

Many of the emotion recognition studies in literature are subject dependent and the limited subject independent emotion recognition studies in the literature report an average of leave one subject out (LOSO) validation result as accuracy. The work reported in this paper sets the baseline for subject independent emotion recognition using DEAP dataset by clearly specifying the subjects used in training and test set. In addition, this work specifies the cut-off score used to classify the scale as low or high in arousal and valence dimensions. Generally, statistical features are used for emotion recognition using physiological signals as a modality, whereas in this work, time and frequency domain features of physiological signals and EEG are used. This paper concludes that valence can be identified from EOG while arousal can be predicted from plethysmograph.

Safety training can effectively facilitate workers’ safety awareness and prevent injuries and fatalities on construction sites. Traditional training methods are time-consuming, low participation, and less interaction, which is not suitable for students who are born in Generation Z (Gen Z) and expect to be positively engaged in the learning process. With the characteristic of immersive, interaction, and imagination, virtual reality (VR) has become a promising training method. The purpose of this study is to explore Gen Z students’ learning differences under VR and traditional conditions and determine whether VR technology is more suitable for Gen Z students.

This paper designed a comparison experiment that includes three training conditions: VR-based, classroom lecturing, and on-site practice. 32 sophomore students were divided into four groups and received different training methods. The eye movement data and hazard-identification index (HII) scores from four groups were collected to measure their hazard-identification ability. The differences between the participants before and after the test were tested by paired sample t-test, and the differences between the groups after the test were analyzed by one-way Welch’s analysis of variance (ANOVA) test.

The statistical findings showed that participants under VR technology condition spent less time finding and arriving at the Areas of Interest (AOIs). Both the eye movement data and HII scores indicated that VR-based safety training is an alternative approach for Gen Z students to traditional safety training methods.

These findings contribute to the theoretical implications by proving the applicability of VR technology to Gen Z students and empirical implications by guiding colleges and universities to design attractive safety training lessons.

The purpose of this study is to investigate buyer actions during source selection that impact the buyer’s reputation.

This study uses survey data of 211 suppliers to empirically test the effects of US Government buyers’ actions on their reputation during source selection.

Suspicion of buyer opportunism diminishes buyer reputation, while debriefing quality positively influences buyer reputation. However, oral presentations, negotiations, the full trade-off source selection method and providing a redacted source selection decision document show no significant association with buyer reputation. In turn, buyer reputation decreases a supplier’s intent to protest the award.

This study underscores the importance of ethical conduct during source selection, emphasizing the detrimental impact of opportunistic behavior on a buyer’s reputation, while also advocating for comprehensive feedback to suppliers and the need for holistic, transparent sourcing procedures.

This study contributes to business-to-business marketing literature by addressing the gap in understanding buyer reputation, highlighting the impact of buyer actions on reputation during source selection. This study develops a framework grounded in signaling theory that incorporates feedback and finds that it may have a multiplicative effect that forms a separating equilibrium.

The authors investigate conditions that drive innovation performance in foreign-owned subsidiaries. The authors study five variables affecting innovation performance: organizational agility and digital capabilities as the main drivers and competencies and embeddedness in internal and external networks as complementary antecedents of innovation.

The authors draw on the neo-configurational perspective and apply fuzzy set qualitative comparative analysis (fsQCA) to empirically test survey data from subsidiaries located in the emerging economies of Thailand and Vietnam.

While the authors find no single condition on its own determining innovation performance, the authors do find that in concert they form four configurations of high innovation performance. The results indicate that all configurations contain competencies, as well as that subsidiaries should prioritize between internal and external networks to complement agility, digital capabilities, to achieve high innovation performance. The authors also reveal intriguing contextual differences in the innovation performance configurations between the two host countries.

By incorporating causal complexity as well as substitutability and complementarity of innovation drivers, the authors extend the current understanding of subsidiary innovation performance outcomes.

This study aims to explore the connections between intellectual capital and academic performance in Lahore, Pakistan’s higher education institutions (HEIs). The research delves into the mediation effect of dynamic capabilities, such as acquisition and exploitation, between intellectual capital and innovation within these educational institutions.

Grounded in the insights from a comprehensive literature review, the methodology uses a pre-tested questionnaire. Faculty members from private universities in Pakistan were chosen as the study's unit of analysis. Using a convenience sampling technique, data was gathered from 342 teachers and then analyzed using Smart (PLS) 3.3.3.

The results demonstrate that intellectual capital positively affects innovation. Acquisition and exploitation further mediate this influence, improving academic performance. Applying the knowledge-based view theory, the study confirmed the significance of all the posited hypotheses, underlining the positive interrelationships within Pakistan’s academic institutions.

The novelty of this research lies in its specific focus on the HEIs in Pakistan, demonstrating how intellectual capital and dynamic capabilities foster innovation, thereby enabling these institutions to maintain a competitive edge in a rapidly evolving educational landscape.

The purpose of this paper is to examine how chief executive officers’ (CEOs) narcissism impacts firm performance and how this, in turn, affects a CEO’s positive rhetorical tone.

The narcissism score is measured by using an analytical composite score for each CEO based on eight factors. The paper uses textual analysis on a sample of 848 CEO letters of US firms over the period 2010–2019. WarpPLS software, version 7.0 was used to conduct structural equation modeling through the partial least squares because a non-linear algorithm exists between CEO narcissism, firm performance and positive tone, and the values of path coefficients moved from non-significant to significant.

The results suggest that performance partially mediates the relationship between CEO narcissism and positive tone. This indicates that not all the positivity expressed by narcissistic CEOs is opportunism; some of it is indeed driven by better performance. The reported findings indicate that firm performance explains one-quarter of a CEO’s positive words, whereas some three-quarters of the positivity is driven by a narcissistic CEO (i.e. opportunism). A comparison of letters signed by highly narcissistic and less narcissistic leaders reveals that among those letters signed by highly narcissistic leaders, firm performance plays a significant mediating role between narcissistic tendencies and positive tone. However, among those with less narcissistic score, there is no evidence that performance mediates the tone and narcissism. Interestingly, both highly narcissistic and less narcissistic CEOs use positive words and optimistic expressions even when their firms perform poorly or negatively.

The results help shareholders be aware that CEOs may opportunistically use their personal characteristics and language to manipulate them. Data limitations about women CEOs were one of the reasons behind the small proportion of women CEOs in this study, making it low in generalizability.

A comprehensive review showed that none of previous studies examined the more ambiguous relationship between a CEO’s narcissist tendency, the firm’s performance, and CEO rhetorical tone. As one set of studies focused on Narcissism → Performance, and the other one on Performance → Tone, this current study completes the picture with Narcissism → Performance → Tone.

The scope of this study is to explore and summarize the pool of dimensions, models and measurement techniques of service quality used in healthcare services and to propose a comprehensive conceptual model for practitioners and researchers.

This research employs a comprehensive review of available literature by using multiple keywords on different electronic repositories using the recommendations of the PRISMA approach for the selection of articles. A critical analysis of available studies helped in compiling a list of core service quality dimensions in healthcare services.

This paper presents a comprehensive account of different dimensions and their measurement items used by various researchers to assess service quality in healthcare systems. Most of the researchers have used SERVQUAL model either in its original or modified form while the others have proposed and used totally different dimensions to assess the service quality in healthcare. Many dimensions are just an existing dimension of SERVQUAL that has undergone a name change while others are completely new. The dimensions used by many researchers have items drawn from more than one dimension of SERVQUAL model. The availability of so many dimensions and models adds to the confusion that researchers and practicing managers experience when determining the appropriate model to be used in their work. To mitigate this confusion, there is a need to develop a comprehensive model; the current work is an attempt to meet this need. Through our analysis, we identify four major service quality dimensions: clinical quality, infrastructural quality, relationship and managerial quality and propose a model named CIRMQUAL.

After exploring all available models in the domain of healthcare, this research presents the best possible areas to enhance the quality of healthcare services. It also enhances the research insights for academicians and working professionals by developing and proposing a comprehensive model for measuring healthcare service quality. The proposed model covers almost all of the service quality dimensions used by other researchers and will make the choice of dimensions/model easy for the future researchers/practitioners interested in measuring and improving the quality of services offered by their healthcare units. Such a comprehensive model has not been developed by any researcher thus far.