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Despite competition and supply-chain disruptions during Covid-19 pandemic (2019–2021), one grocery retailer consistently thrived and was ranked top. The sources of the sustained performances needed examination. Guided by self-congruity theory and integrating three models, the authors examined how much the retailer's brand performances (brand loyalty, equity, preference and repurchase intentions) were emanating from brand personalities and marketing offerings. The mediating roles of brand loyalty and equity were tested.

Cross-sectional data was collected from 480 frequent customers using an online questionnaire posted on the researchers' social media pages. Factor analysis was conducted to identify the dimension that best describes the grocery retailer. Partial least square–structural equation modelling (PLS-SEM) was used to test a conceptual model.

Factor analysis results show that brand sincerity (28.582% variance-explained; M = 4.1) was top (factor 1), followed by excitement (20.336% variance-explained; M = 3.9) and then trustworthiness (18.854% variance-explained; M = 3.87). PLS-SEM results revealed that two brand personalities (brand excitement and trustworthiness) and marketing offerings (price, place, product, promotion) impacted loyalty found to be a strong driver of brand equity. Repurchase intention and brand preference were influenced by brand equity. Brand loyalty mediated most of the relationships between brand personality dimensions, marketing offerings and brand equity. Brand equity also significantly mediated the relationships between brand loyalty, preference and repurchase intentions. The integrated model produced high explanatory powers with brand equity (67.8%), brand preference (71.7%), brand loyalty (63.2%) and repurchase intentions (54.2%).

The study extends a brand personality-loyalty model through integrating two other models that provided marketing offerings and brand equity outcomes. It demonstrates that a stream of profitable customers' responses awaits a retailer who holds both brand and customer mindsets by building admired brand personalities while providing desired marketing offerings.

Enormous amount of biomedical wastes (BMW) produced everyday across the world. Management of BMW depends on adherence to protocol. BMW management at generation point, definitely, depends upon the awareness, attitudes and practises of health-care staff, the purpose of this study will assess the awareness, attitude and practise regarding different aspects of BMW.

An observational with appropriate checklists, and a cross-sectional study, involving questionnaires, was conducted during 7-24 January 2016. The existing system of BMW management, funds, resources, etc., knowledge, attitude and practises about BMW were assessed amongst 273 health-care workers in selected public health-care institutes of Karnataka.

Of 273 study participants, majority (54%) of them have not received any training pertaining to BMW. The results showed a poor level of knowledge and awareness of BMW management amongst health-care personnel. Merely, 43% of the participants correctly knew the categorization of BMW and its disposal in proper colour-coded bins/bags. Awareness is very poor amongst the lower age group, male participants, lab-technicians/pharmacists and supporting staff. Doctors were good at theoretical knowledge such as rules, legislation and public-health importance of BMW management than the practical aspects such as categorization and colour-coding. Further, the attitude of health-care staff is favourable about BMW. Immunization for hepatitis-B was very poor amongst waste handlers (43%).

As the awareness and practise regarding BMW management were poor across different health-care staff there is a need to conduct periodic training and regular monitoring with special focus on the proper use of personal protective equipment. Further, precautionary immunization should be provided, especially waste handlers and sanitary workers.

Stock markets are considered as the largest and most important units for the development and growth of the economy. The present study attempts to provide a comprehensive view of factors influencing investment decision making process of stock market investors. A multi group analysis of gender is also carried out on the proposed model.

The data of 402 valid responses are collected through structured questionnaires from individual investors of North India. SPSS 23 is used to do the descriptive analysis and AMOS 22 is used to establish the validity of the constructs and for hypotheses testing. For performing multi group analysis, several invariance tests have also been conducted to check the robustness of the model.

The results reveal that all the factors such as firm image, accounting information, neutral information, advocate recommendation and personal financial needs significantly influence investment decision making concluding image of the firm being the most influential factor and advocate recommendation being the least influential factor for investment decisions. No significant differences between males and females were found.

The current study suffers from the limitation of restricted geographical area of North India. Moreover, there is also a scope to incorporate more demographic factors for predicting investment decisions.

This study incorporates a range of factors which covers all the aspects of investment decision making. This study also highlights the notion of signaling theory, thus contributing to the limited literature in Indian context.

Although health-related quality of life (HRQOL) has become an important outcome, specifically in regard to the impact of illness and treatment in patients with depression, few studies have explored the HRQOL of patients from different types of hospitals. This study aimed at examining a change in HRQOL of patients from various types of hospitals

A repeated measure was used in this study. Thirty participants in psychiatric outpatient units per center from the different types of hospitals, including a psychiatric hospital, regional hospital, general hospital and community hospital, were assessed with the Thai version of the World Health Organization Quality of Life Brief (WHOQOL-BREF-THAI) questionnaire at the first visit, and after the 6th and 12th weeks of the treatment course.

The HRQOL scores for the participants were increased in each type of hospital from their first visit to the 6th week and 12th week (p < 0.001; except for the 6th week in the regional hospital, p < 0.01).

The findings reflected HRQOL in patients with depression in terms of the resources available in different types of hospitals that could be used as baseline data for the development of Thai mental health service systems.

Emojis are quickly becoming a popular new language in social media and marketing. The capability to express emotions and make message understanding easier is one of the primary reasons for using emojis. The aim of this research was to determine the influence of perceived usefulness, perceived ease of use, trust, and involvement on customer engagement due to emojis used in digital marketing communications among Generation Z (Gen Z) in South Africa.

Following the descriptive research approach, quantitative research was used in this study. A questionnaire (self-administered) was utilized to test the effectiveness of using emojis among 1,000 young consumers. Structural equation modeling was used to test the hypotheses.

The findings of the study yielded positive relationships between the variables, namely between trust and involvement; involvement and the perceived ease of use; involvement and perceived usefulness; perceived ease of use and perceived usefulness; trust and customer engagement; perceived usefulness and customer engagement; involvement and customer engagement; customer engagement and intention to purchase; trust and intention to purchase; and perceived usefulness and intention to purchase.

This study can help organizations in emerging markets use emojis in their digital marketing communications to engage customers and stimulate intention to purchase among young people, especially the Gen Z cohort, who seek organizations and brands that understand and connect with them.

By investigating the effects of emojis in digital marketing communications, this study contributes to the customer-centric process and the literature on emoji usage while also involving a credible digital language when communicating with members of Gen Z. By extending TAM, the findings of this study contribute to the TAM literature by demonstrating that emoji usage in digital marketing communications positively influences various attitudinal associations among Gen Z consumers.

This study identifies key facets leading to consumers' Internet of Things (IoT) adoption intention.

Applying four technology acceptance theories (theory of planned behavior, technology acceptance model, pleasure-arousal-dominance theory and technology readiness index), the author uses deductive quantitative research to develop a model, explaining IoT adoption intentions. Administrated questionnaires are distributed in Egypt among generation-Z and millennials in malls. A total of 400 questionnaires are used for hypotheses testing, applying structural equation modeling (SEM) path coefficient analysis.

Results of this study show that attitude, dominance, perceived usefulness, innovativeness and insecurity impact consumers' IoT adoption intentions; subjective norms, perceived behavior control, pleasure, arousal, perceived ease, optimism and discomfort hold insignificant impact on consumers' IoT adoption intentions.

Exploring IoT facets and how these facets impact consumers' adoption intentions, this study helps grasp technology acceptance in theory and practice, guiding scholar and practitioners (e.g. IoT developers, retailers, marketers and other field experts) to consider consumers' mindset when developing, improving and marketing IoT.

The contribution stems from the incorporation of various frameworks used to explain technology acceptance. By studying several theories jointly, the research extracts and identifies a significant set of facets (technical and psychological) to build a comprehensive theory of IoT acceptance, showing consumers' IoT adoption is not entirely similar to adoption of other past innovations. This understanding allows marketers to focus on content that needs to be promoted to boost consumers' IoT purchase plans. Future researchers could replicate the results to IoT categories (e.g. home appliances, cars, healthcare, education, sportswear, etc.) to improve external validity of the findings, among other future research opportunities.

This study aims to investigate the specific difficulties involved in implementing electronic recordkeeping for anti-corruption investigations in Nigeria. It recognises the importance of technological advancements in such investigations and the need for efficient, internationally recognised services, especially in a country where manual processes are prevalent.

This study uses a qualitative, exploratory case study approach. Data were gathered through interviews with 15 anti-corruption investigators in Nigeria in the year 2020 and analysed using thematic analysis.

This study identified two main challenges: resistance to adopting technological change and indifference towards information technology.

This study highlights the transformative potential of technology, specifically cloud computing and forensic technology, in an investigative context. By intentionally integrating technology, existing deficiencies can be addressed, investigative processes can be streamlined and a culture of accountability can be cultivated. It contributes to ongoing discussions and emphasises the capacity of technology to drive significant transformation in the pursuit of integrity and justice.

This study aims to empirically analyze the factors influencing users’ intention to use chatbots for airline ticket consultation. It seeks to introduce a comprehensive framework based on the technology acceptance model (TAM) that integrates key factors alongside traditional TAM constructs to understand what drives behavioral intention to use chatbots in the context of airline ticket consultation.

The study uses the partial least squares-structural equation modeling (PLS-SEM) approach to validate the proposed model empirically. Data were collected through a survey questionnaire distributed to potential users in Saudi Arabia, with 393 valid responses from a total of 409 received being included in the analysis.

The empirical analysis confirms the significance of perceived usefulness and user satisfaction as direct determinants of behavioral intention. Additionally, it reveals that factors such as perceived ubiquitous access, perceived completeness, perceived accuracy, perceived unbiased response and perceived convenience have both direct and indirect significant impacts on the behavioral intention to use chatbots for airline ticket consultation.

This research advances theoretical understanding and holds practical implications for designing and implementing effective chatbot services. By investigating the complex interplay of these factors, the study makes substantive contributions to both theoretical advancements and practical applications in the field, particularly in enhancing the user experience and acceptance of chatbots for airline ticket consultations.