International Journal of Business Ecosystem & Strategy

The rapid advancement of information and communication technologies has profoundly transformed urban governance and tourism development worldwide, giving rise to the concepts of Smart City and Smart Tourism as integrated models of sustainable innovation. In Indonesia, several local governments have adopted Smart City initiatives to enhance public service quality and economic competitiveness. Among them, Bekasi Regency has emerged as one of the leading regions in formulating a comprehensive Smart Tourism planning framework. This study aims to examine the key dimensions of Smart Tourism planning in Bekasi by analyzing how digital transformation, governance innovation, and technological integration are embedded within the regional development agenda. Employing a qualitative approach that combines literature review and in-depth interviews with members of the Bekasi Smart City Council, this research utilizes thematic analysis through NVivo software. The findings indicate that technology and innovation form the core of Bekasi’s Smart Tourism planning, emphasizing three interrelated components: Smart Experience, Smart Business Ecosystem, and Smart Destination. The study also reveals that although digital infrastructure and public service systems have been significantly developed, challenges remain in data management, interoperability, and community digital literacy. It concludes that effective Smart Tourism planning should prioritize data-driven governance, cross-sector collaboration, and community empowerment to strengthen tourism competitiveness and ensure sustainable regional development.

This study examines the causes of marketing performance stagnation in a mature and highly competitive industry context and investigates how segmentation, targeting, and positioning (STP) decisions can be reconfigured to support performance recovery. Using empirical analysis of customer transaction and behavioral patterns, the findings reveal that market value is highly concentrated within core segments characterized by stable and repeated purchasing behavior. However, these behavioral insights have not been systematically translated into coordinated STP decisions, resulting in unfocused targeting and generic positioning.  To address this gap, the study proposes a behavior-driven STP approach that reconceptualizes STP as an adaptive decision system rather than a static market planning framework. Under this approach, segmentation serves to identify value structures based on observed customer behavior, targeting functions as a strategic resource allocation decision derived from behavioral intensity and stability, and positioning reflects the consumption context and behavioral motives of core segments.  The study contributes to the industrial marketing management literature by demonstrating how behavior-driven STP operates as an adaptive marketing capability that enables firms to restore strategic coherence and improve marketing effectiveness following organizational and environmental disruptions. Managerially, the findings suggest that firms should institutionalize the use of behavioral customer data, narrow strategic focus toward high-value core segments, and align value propositions with actual usage contexts to enhance performance sustainability in dynamic market environments.

Understanding the determinants of Battery Electric Vehicle (BEV) purchase intention in emerging markets requires rigorous empirical investigation. This study examines the key factors that discriminate between consumers who express interest and those who remain unwilling to purchase BEVs in Indonesia. Using survey data from 281 respondents, discriminant analysis was conducted to assess the influence of product attributes, price perceptions, and demographic characteristics on consumer behavioral intentions. Cross-validation results indicate a hit ratio of 79.4%, surpassing the proportional chance criterion of 63.36%, thereby confirming the model’s predictive validity. The findings reveal that the relatively high upfront purchase price is the strongest discriminating factor, followed by income level and product performance, suggesting that economic evaluations and functional value appraisals dominate consumer decision-making processes. Additional economic considerations—government incentives and operational costs—also significantly differentiate consumer groups. In contrast, demographic variables such as education, age, and gender exhibit limited discriminant power, although younger consumers demonstrate greater openness to BEV adoption. Overall, the results indicate that BEV purchase intention in Indonesia is primarily shaped by cost-related perceptions and assessments of functional product value. Future studies are encouraged to incorporate psychological constructs and utilize longitudinal designs to capture behavioral dynamics over time.

The rapid advancement of information and communication technologies has profoundly transformed urban governance and tourism development worldwide, giving rise to the concepts of Smart City and Smart Tourism as integrated models of sustainable innovation. In Indonesia, several local governments have adopted Smart City initiatives to enhance public service quality and economic competitiveness. Among them, Bekasi Regency has emerged as one of the leading regions in formulating a comprehensive Smart Tourism planning framework. This study aims to examine the key dimensions of Smart Tourism planning in Bekasi by analyzing how digital transformation, governance innovation, and technological integration are embedded within the regional development agenda. Employing a qualitative approach that combines literature review and in-depth interviews with members of the Bekasi Smart City Council, this research utilizes thematic analysis through NVivo software. The findings indicate that technology and innovation form the core of Bekasi’s Smart Tourism planning, emphasizing three interrelated components: Smart Experience, Smart Business Ecosystem, and Smart Destination. The study also reveals that although digital infrastructure and public service systems have been significantly developed, challenges remain in data management, interoperability, and community digital literacy. It concludes that effective Smart Tourism planning should prioritize data-driven governance, cross-sector collaboration, and community empowerment to strengthen tourism competitiveness and ensure sustainable regional development.

This study examines the causes of marketing performance stagnation in a mature and highly competitive industry context and investigates how segmentation, targeting, and positioning (STP) decisions can be reconfigured to support performance recovery. Using empirical analysis of customer transaction and behavioral patterns, the findings reveal that market value is highly concentrated within core segments characterized by stable and repeated purchasing behavior. However, these behavioral insights have not been systematically translated into coordinated STP decisions, resulting in unfocused targeting and generic positioning.  To address this gap, the study proposes a behavior-driven STP approach that reconceptualizes STP as an adaptive decision system rather than a static market planning framework. Under this approach, segmentation serves to identify value structures based on observed customer behavior, targeting functions as a strategic resource allocation decision derived from behavioral intensity and stability, and positioning reflects the consumption context and behavioral motives of core segments.  The study contributes to the industrial marketing management literature by demonstrating how behavior-driven STP operates as an adaptive marketing capability that enables firms to restore strategic coherence and improve marketing effectiveness following organizational and environmental disruptions. Managerially, the findings suggest that firms should institutionalize the use of behavioral customer data, narrow strategic focus toward high-value core segments, and align value propositions with actual usage contexts to enhance performance sustainability in dynamic market environments.

Understanding the determinants of Battery Electric Vehicle (BEV) purchase intention in emerging markets requires rigorous empirical investigation. This study examines the key factors that discriminate between consumers who express interest and those who remain unwilling to purchase BEVs in Indonesia. Using survey data from 281 respondents, discriminant analysis was conducted to assess the influence of product attributes, price perceptions, and demographic characteristics on consumer behavioral intentions. Cross-validation results indicate a hit ratio of 79.4%, surpassing the proportional chance criterion of 63.36%, thereby confirming the model’s predictive validity. The findings reveal that the relatively high upfront purchase price is the strongest discriminating factor, followed by income level and product performance, suggesting that economic evaluations and functional value appraisals dominate consumer decision-making processes. Additional economic considerations—government incentives and operational costs—also significantly differentiate consumer groups. In contrast, demographic variables such as education, age, and gender exhibit limited discriminant power, although younger consumers demonstrate greater openness to BEV adoption. Overall, the results indicate that BEV purchase intention in Indonesia is primarily shaped by cost-related perceptions and assessments of functional product value. Future studies are encouraged to incorporate psychological constructs and utilize longitudinal designs to capture behavioral dynamics over time.