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The digital marketing landscape is rapidly evolving, but the integration of visual content still heavily depends on human expertise. Driven by the quest for innovative marketing strategies that resonate with family-oriented consumers, this study seeks to bridge this gap by applying machine learning to analyze visual content in the maternity and baby care product sector.

This study incorporates a range of machine learning techniques – including open science framework feature detection, panoptic segmentation, customized instance segmentation, and face detection calculation methods – to analyze and predict the appeal of images, thereby enhancing user engagement and parent-child intimacy.

The exploration of various ML models, such as DT, LightGBM, RIPPER algorithm, and CNNs, has offered a comparative analysis that addresses a methodological gap in the existing literature, which frequently depends on isolated model evaluations. According to our quadrant analysis with respect to engagement rate and parent-child intimacy, the selection of a model for real-world applications depends on balancing performance and interpretability.

The proposed system offers a series of actionable recommendations designed to enhance customer engagement and foster brand loyalty. This study contributes to image design in maternity and baby care marketing and provides analytical insights for recommendation systems.

This study aims to investigate the drivers of halal-certified firms in Taiwan, a Muslim minority country, to provide halal products or services.

This study used a quantitative method by spreading offline and online surveys toward halal-certified firms in Taiwan. Data were obtained from 41 responses and were analyzed using partial least square structural equation modeling.

This study discovers that firms in Taiwan practice halal business as they possess halal perceived value and innovation orientation. In addition, the interplays of the antecedents, the internal and external drivers, also play an excellent role in shaping the firms’ practices on halal business.

Despite the implications, this study was built under several limitations that are potentially addressed by future research. The limitations lay in the low response rate, indistinctive analysis based on the firms’ market orientations (domestic or international) and the exclusion of other relevant variables to the conceptual model.

Practically, this study clarifies that firms in a Muslim minority country can be encouraged to engage in halal business in several ways. Those with a good understanding of halal usefulness are oriented to innovation, exposed to external pressures about halal business and equipped with specific internal settings that can translate the halal business phenomenon as an opportunity, not a threat.

To the best of the authors’ knowledge, this study is the first to unveil the drivers of halal business practices of firms in a Muslim minority country.

Resource scarcity is a major difficulty facing firms that engage in new product development (NPD) projects. The purpose of this paper is to understand how resource allocation strategies affect NPD performance and which strategy is the best alternative, a research and development (R&D) process model is constructed using system dynamics.

Moreover, resource allocation strategies are categorized into two types: design‐stage‐first strategy and manufacturing‐stage‐first strategy, and several important indicators of performance evaluation are defined. Then different workload scenarios are developed to test the relationships between resource allocation strategy and various NPD performance measures.

The most important finding from simulation results is that a firm should allocate its resources into early development stage first in order to obtain superior R&D performance.

This paper has successfully constructed new system dynamics model for quantifying the performances of R&D process.

This study aims to examine the location determinants of market expansion of the biotechnology industry to China’s second-tier cities.

The authors involved 68 top management officials of biopharmaceutical firms in China by applying triangulation data collection, which comprises depth interview, questionnaire survey and focus group discussion.

Data collection results reveal the following: 20 location determinants are determined and categorized into 5 clusters (i.e. 3 cost/tax factors, 5 demand factors, 1 macroeconomic factor, 3 socio-political factors and 8 strategic factors); among these 20 factors, 9 factors contribute to firm benefits, 5 factors open opportunities for business growth and 6 factors pose potential risks.

This study proposes a framework of location determinants for biotech pharmaceutical industry in expanding second-tier cities of China market. The findings of this study can be used as a reference for multinational companies, specifically in market expansion to second-tier cities in China.