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This paper aims to use Q methodology to investigate Millennial perceptions toward private label or national brand apparel.

Q methodology was chosen to identify factors, which correspond to patterns of perceptions prevalent among Millennials. Participants were supplied with 14 statements that they sorted into two Q sorts – One representing perceptions of private label and the other representing perceptions of national brands. The Q sorts were completed through Qualtrics and participants answered open-ended questions on the placement of each statement within each Q sort.

Two factors emerged on private labels, highlighting patterns in price consciousness and uniqueness (acknowledged as patterns surrounding the desire for particular apparel characteristics). Three factors arose for national brand apparel, emphasizing the need for national brands to provide consumers with product security, quality and uniqueness (as identified through the unpreferred qualities national brands typically exhibit).

This study illustrates the various viewpoints retailers must consider when marketing apparel to a specific target demographic. In addition, a single perception (uniqueness) was found to connect motivations, which led to the development of a model for future inquiry.

Despite complete Q sorts and qualitative statements, participants' unfamiliarity with Q methodology and the sorting action of statements could be considered a limitation. The use of MTurk is also considered a limitation owing to the anonymity and possible deception of the workforce.

Private label brand personality growth has many retailers expanding their brand portfolios. Based on the findings of this study, specific opportunities are highlighted for the expansion and marketing of private labels and brand labels based on specific perceptions of a broad Millennial cohort.

Grounded in strategic fit theory, this study aims to identify external and internal factors that influence retailers’ strategic choices regarding their own product brands. Furthermore, it seeks to explore the variations between different own product brand strategies in achieving both external and internal strategic fit.

The systematic review method, incorporating a thematic analysis, was adopted, and 318 articles were included for review.

The factors that influence retailers’ strategic choices regarding their own product brands encompass a range of external macro and industrial environmental factors, along with various internal resource and capability factors. Moreover, the effects of these factors vary across different own product brand strategies.

To our knowledge, this is the first systematic review of research on retailers’ own product brands from a strategic management perspective, offering systematic and structured guidance for retailers.

Although many scholars have acknowledged inconsistencies in the use of the retail brand term within the existing empirical literature, no one has conducted a systematic study to clarify the confusion of terms. Aiming at unifying the use of terms, this study aims to explore the terms that best express each retail brand concept, and discusses the definitions of proposed terms that can distinguish the connotation of different retail brand concepts.

Through a systematic review, 463 articles were obtained, from which retail brand terms and their definitions were further extracted. Semantic analysis and content analysis were adopted to analyze terms and definitions, respectively.

Semantically, the terms that best express four levels of retail brand concepts are own product brand, store brand, platform brand and retailer brand. Six key elements to distinguish different levels of a retail brand are identified through the content analysis of definitions, and on this basis, four proposed terms are defined.

Noting that no study focuses on the conceptual confusion of retail brands in recent decades, the findings are expected to clarify the confusion of terms and unify the use of terms, hence facilitating the communication between scholars and the sharing of research results.

The purpose of this paper is to study haemodynamic flow characteristics and entropy analysis in a bifurcated artery system subjected to stenosis, magnetohydrodynamic (MHD) flow and aneurysm conditions. The findings of this study offer significant insights into the intricate interplay encompassing electro-osmosis, MHD flow, microorganisms, Joule heating and the ternary hybrid nanofluid.

The governing equations are first non-dimensionalised, and subsequently, a coordinate transformation is used to regularise the irregular boundaries. The discretisation of the governing equations is accomplished by using the Crank–Nicolson scheme. Furthermore, the tri-diagonal matrix algorithm is applied to solve the resulting matrix arising from the discretisation.

The investigation reveals that the velocity profile experiences enhancement with an increase in the Debye–Hückel parameter, whereas the magnetic field parameter exhibits the opposite effect, reducing the velocity profile. A comparative study demonstrates the velocity distribution in Au-CuO hybrid nanofluid and Au-CuO-GO ternary hybrid nanofluid. The results indicate a notable enhancement in velocity for the ternary hybrid nanofluid compared to the hybrid nanofluids. Moreover, an increase in the Brinkmann number results in an augmentation in entropy generation.

This study investigates the flow characteristics and entropy analysis in a bifurcated artery system subjected to stenosis, MHD flow and aneurysm conditions. The governing equations are non-dimensionalised, and a coordinate transformation is applied to regularise the irregular boundaries. The Crank–Nicolson scheme is used to model blood flow in the presence of a ternary hybrid nanofluid (Au-CuO-GO/blood) within the arterial domain. The findings shed light on the complex interactions involving stenosis, MHD flow, aneurysms, Joule heating and the ternary hybrid nanofluid. The results indicate a decrease in the wall shear stress (WSS) profile with increasing stenosis size. The MHD effects are observed to influence the velocity distribution, as the velocity profile exhibits a declining nature with an increase in the Hartmann number. In addition, entropy generation increases with an enhancement in the Brinkmann number. This research contributes to understanding fluid dynamics and heat transfer mechanisms in bifurcated arteries, providing valuable insights for diagnosing and treating cardiovascular diseases.

The new ways of working (NWW), a contemporary work environment with temporal and spatial flexibilities, has become an enforced reality after the COVID-19 pandemic disrupted workplaces. However, the understanding of how it impacts employee well-being perceptions is limited. Hence, the current study aims to examine how the NWW facets, namely, time- and location-independent work, management of output, access to organizational knowledge and flexibility in working relations relate to employees' life satisfaction, mediated by psychological capital.

A cross-sectional survey was designed to collect data from 459 Indian knowledge workers. Model fit and the hypothesized relationships were tested using IBM SPSS 25, AMOS and PROCESS Macro.

All four NWW facets positively relate to psychological capital, which in turn associates with life satisfaction. Except for the facet “management of output”, the other three facets associate positively with life satisfaction before accounting for the mediator. Indirect effects of all four facets on life satisfaction via psychological capital were established. Overall, the findings establish the important mediating role of psychological capital in relating the NWW facets with life satisfaction.

By examining the previously unexplored relationships between NWW, psychological capital and life satisfaction, this study provides novel insights into the role of personal resources in maximizing the beneficial effects of the NWW practices and is highly relevant in the current context where organizations are trying to identify coping mechanisms that help employees adapt to workplace transformations.

This study aims to examine the complex relationship between the personality meta-traits of stability and plasticity and time-based work–family conflict (WFC). Stability and plasticity are hypothesized to influence WFC directly and indirectly, via boundary strength at work (BSW) and boundary strength at home (BSH) domains. WFC has two dimensions – conflict due to family interfering in work (FIW) and conflict due to work interfering in family (WIF).

Data was collected from 419 full-time employees in multiple US companies. Hypotheses were tested using structural equation modeling.

Stability was associated with lower levels of WFC and stronger boundaries around the work and home domains. BSW mediated the relationship between stability and FIW; BSH mediated the relationship between stability and WIF. plasticity was associated with weaker boundaries around the work and home domains. BSW and BSH had a negative relationship with FIW and WIF, respectively.

The study is cross-sectional and limited to time-based work–family conflict. The results support the adoption of a more agentic view of personality in the boundary setting and WFC literatures.

Employers need to design flexible work programs that offer employees control over work–home boundary strength.

The study links stability and plasticity to WFC. It expands the nomological network of work–home boundaries.

Work overload has become a relevant issue in the Information Technology (IT) industry, with negative effects for individuals and organizations alike. This study aims to analyse the role of personal resources in a broad model regarding the effects of work overload on performance and well-being for the particular case of IT professionals. Considering the specificities of the IT industry, three personal resources were included in this study: one stable personality variable (conscientiousness) and two more malleable variables (work-life balance and psychological detachment).

To test the model, the authors use a sample of 144 IT Portuguese professionals. The authors collected data through an online questionnaire shared in social networks and IT social network communities. The authors use partial least squares (PLS) for data analysis.

The results show that work overload negatively impacts on employees’ life satisfaction, psychological detachment, work-life balance and task performance. Conscientiousness is positively related with two positive outcomes: task performance and life satisfaction. Work-life balance has a mediating effect in the relationship between work overload and life satisfaction.

These findings emphasize the need to promote conscientiousness in IT professionals, as well as reduce workload and promote family-friendly working environments to foster work-life balance and life satisfaction.

By testing this model, the authors aim to contribute to the current knowledge on the role of personal resources in the Job Demands-Resources model, which is still unclear and under-researched.

The Indian pharmaceutical industry has contributed significantly to global healthcare by securing superior-quality, inexpensive and reachable medicines worldwide. However, supply chain management (SCM) has been challenging due to constantly shifting requirements for short lifecycles of products, the convergence of industry and changeable realities on the ground. This study aims to identify, assess and prioritize the strengths, weaknesses and opportunities of the pharmaceutical SCM environment in India.

The paper employs a Strength, Weakness, Opportunity, Threat (SWOT) analysis and recognizes strategies to utilize the advantages of the strengths and opportunities, rectify weaknesses and resolve threats.

A variety of strategies that could have a positive effect on the Indian pharmaceutical business are presented. Findings and suggested strategies can significantly advance knowledge, enhance understanding and contribute to the growth of a successful SCM for the Indian pharmaceutical sector.

This paper would act as a roadmap to greater comprehension of the market leaders and market leaders' operating climate. The findings from this study will offer academic scholars and business practitioners deeper insights into the environment of SCM.

This study aims to assess the impact of personality traits, risk perception and perceived coronavirus disease 2019 (COVID-19) disruption on the investment behavior of individual investors in the Indian stock market.

This study adopts a survey approach. The sample comprises 315 active retail investors investing in the Indian stock exchange. Two-stage analysis technique regression and Artificial Neural Network (ANN) were used for data analysis. Study hypotheses were tested through regression and ANN was adopted to validate the regression results.

Two regression models were modeled to test the research hypotheses. Findings showed that risk perception and COVID-19 disruption have a significant positive and neuroticism has a significant negative impact on short-term investment decisions, while the role of conscientiousness in determining short-term investment decisions was not found significant. Results also showed a positive impact of neuroticism and conscientiousness and a negative impact of risk perception on long-term investment decisions. The role of COVID-19 disruption was found negative but insignificant in predicting long-term investment decisions.

This study has practical implications for many parties like retail investors, financial advisors and policymakers. This study will assist the investors to realize that they do not always take rational financial decisions. This study will suggest the financial advisors to use the knowledge of behavioral finance in making the advisors' advisory and wealth management decisions. This study will also assist the policymakers to outline behaviorally well-informed policy decisions to protect the interests of investors.

India is one of the fast-growing economies in the world. India has a vast population of active investors and determining investors' investment behavior adds novelty to this study as developed economies have remained the main focus of previous studies. The other novel feature of this study is that this study tries to assess the impact of COVID-19 disruption along with personality traits and risk perception on investment behavior. The other valuable factor of this study is the use of ANN to predict the relative importance of the exogenous variables.

This study aims to reduce data bias during human activity and increase the accuracy of activity recognition.

A convolutional neural network and a bidirectional long short-term memory model are used to automatically capture feature information of time series from raw sensor data and use a self-attention mechanism to learn select potential relationships of essential time points. The proposed model has been evaluated on six publicly available data sets and verified that the performance is significantly improved by combining the self-attentive mechanism with deep convolutional networks and recursive layers.

The proposed method significantly improves accuracy over the state-of-the-art method between different data sets, demonstrating the superiority of the proposed method in intelligent sensor systems.

Using deep learning frameworks, especially activity recognition using self-attention mechanisms, greatly improves recognition accuracy.