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Given that existing retail brand research tends to treat each level of a retail brand as a separate concept, this paper aims to unveil the holistic nature of a multi-level retail brand, considering the distinctiveness of each level and the interrelationships between the images of different levels.

This study uses a scoping review approach that includes 478 retail brand articles. Subsequently, a thematic analysis method is applied.

The brand attributes that shape the distinct image of each retail brand level encompass diverse intrinsic and extrinsic attributes. Moreover, the holistic nature of a multi-level retail brand is formed by the interrelationships between the images of different levels, which are reflected in the presence of common extrinsic attributes and their interplay at attribute, benefit and attitude levels.

Theoretically, this review provides conceptual clarity by unveiling the multi-level yet holistic nature of a retail brand, helping researchers refine and extend existing theories in retail branding, while also providing new research opportunities in this field. Practically, the findings could guide retailers in implementing differentiated branding strategies at each level while achieving synergy across all levels.

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 improve the accuracy of the facial expression recognition by using genetic algorithm (GA) with an appropriate fitness evaluation function and Pareto optimization model with two new objective functions.

To achieve facial expression recognition with high accuracy, the Haar-like features representation approach and the bilateral filter are first used to preprocess the facial image. Second, the uniform local Gabor binary patterns are used to extract the facial feature so as to reduce the feature dimension. Third, an improved GA and Pareto optimization approach are used to select the optimal significant features. Fourth, the random forest classifier is chosen to achieve the feature classification. Subsequently, some comparative experiments are implemented. Finally, the conclusion is drawn and some future research topics are pointed out.

The experiment results show that the proposed facial expression recognition algorithm outperforms ones in the existing literature in terms of both the actuary and computational time.

The GA and Pareto optimization algorithm are combined to select the optimal significant feature. To improve the accuracy of the facial expression recognition, the GA is improved by adjusting an appropriate fitness evaluation function, and a new Pareto optimization model is proposed that contains two objective functions indicating the achievements in minimizing within-class variations and in maximizing between-class variations.

This study tries to examine the factors that influence the adoption of e-governance mobile applications among Indian citizens. In addition, this study aims to analyse the impact of these factors on the adoption process.

The study used convenience sampling procedure to collect the data from 431 citizens of India. Confirmatory factor analysis and structural equation modelling techniques were used to assess the validity of scale and test the hypotheses.

The finding reveals that the information quality (IQ), perceived usefulness, social influence and government appeal (GA) significantly and positively impacted the attitude of citizen towards the m-governance. In addition, perceived ease of use was not significantly and positively impacted the citizen towards the m-governance.

This study aims to contribute to the existing literature on m-governance adoption in the developing nation. The study intends to provide insightful information on the factors influencing the adoption of m-governance. Also, this study seeks to make a scholarly contribution and provide practical insights for professionals in the industry and government departments.

Mobile applications transform the government operations and enhance the efficiency of government service delivery. Although there are numerous benefits of m-government application, but still the adoption rate of m-governance is steady. The study uses technology acceptance model along with incorporated two additional constructs, i.e. IQ and GA, to make model more comprehensive and robust to understand the m-governance adoption intention.