Journal of New Approaches in Management and Marketing

Abstract The current research was conducted with the aim of analyzing the mediating role of organizational ambidexterity in the effect of corporate social responsibility and knowledge management infrastructure on sustainable performance. The research is based on the objective, applied, and in terms of method, survey. The statistical population was made up of all the managers and experts of the staff of Dr. Tamin Company, numbering 300 people. Based on the simple random sampling method and Cochran's formula, 168 people were selected as a sample. The data collection tool was a standard questionnaire whose validity was confirmed using the opinions of experts in the field of management and its reliability through Cronbach's alpha. Data were analyzed using structural equation model in SmartPLS3 software. The findings of the research showed that the value of the coefficient of the path of corporate social responsibility on organizational ambidexterity is equal to 0.417, with the T statistic (5.081); The value of the coefficient of the path of knowledge management infrastructure on organizational ambidexterity is equal to 0.379, the value of the coefficient of the path of social responsibility on sustainable performance is equal to 0.513, with the T statistic (11.980); The value of the path coefficient of knowledge management infrastructure on sustainable performance was equal to 0.439, the value of the path coefficient of organizational ambidexterity on sustainable performance was equal to 0.571, which were significant at the 95% confidence level. Also, the results showed that organizational ambidexterity can mediate the effect of social responsibility on sustainable performance to the extent of 0.751. In addition, organizational ambidexterity can mediate the effect of knowledge management infrastructure on sustainable performance to the extent of 0.655.

Abstract This research aims to investigate the experiences and characteristics that influence the transition of young individuals' career trajectories from traditional employment to freelancing. The statistical population of this study comprises 28 Iranian specialists in freelancing. The data were gathered using semi-structured interviews with purposive sampling and continued until theoretical saturation was achieved. This qualitative research employs thematic analysis based on the framework established by Braun and Clarke, with coding and analysis performed using Atlas.ti software. The study of the findings identifies four strategic characteristics that offer a thorough picture of freelancing. The initial dimension encompasses the push factors and decision-making in career transitions; the second pertains to substantial economic and financial obstacles during the transition process; the third involves skill development and professional networking; and the fourth addresses the economic empowerment outcomes for youth. The findings suggest that the shift from employment to freelancing is a complex, multifaceted process necessitating meticulous planning, the cultivation of robust social and professional networks, and the establishment of a supportive political and governmental framework. This extensive strategic framework outlined in this research can function as a valuable scientific and practical resource for policymakers, entrepreneurs, and stakeholders, such as chambers of commerce and labor unions, to effectively assist young individuals in their career transitions and foster improved conditions for the advancement of freelancing.

Abstract The aim of this study is to explore artificial intelligence in the automotive industry through a bibliometric analysis, a systematic review, and future research directions. In this study, 179 international articles indexed in the Web of Science and Scopus databases were analyzed. The research methodology consisted of two stages: first, a bibliometric analysis was conducted using VOSviewer software to identify thematic clusters in the literature related to artificial intelligence and the automotive industry. Subsequently, a qualitative systematic review was carried out to provide deeper insights into these clusters.The findings revealed a significant focus on autonomous vehicles, deep learning, and machine learning as key AI technologies. Four thematic clusters were identified, including AI-driven automotive ecosystems, core AI technologies and security, connectivity and resource management, and advanced vehicle technologies. In particular, safety, resource optimization, and regulatory frameworks emerged as key areas within these clusters. The study also identified four emerging research domains that are expected to play a major role in shaping the future of artificial intelligence in the automotive industry, while offering transformative opportunities to address existing knowledge gaps.

Abstract This study aims to systematically identify and refine the components of audience-centricity in the arts, . Employing an exploratory sequential mixed-methods approach, the research was conducted in two main phases. In the qualitative phase, using purposive sampling, 19 authoritative scientific articles were subjected to in-depth analysis through qualitative content analysis facilitated by NVIVO software yielded 39 initial codes, nine axial categories, and ultimately four core components. In the quantitative phase, fuzzy screening technique was employed to refine the components within the specialized context of the arts, utilizing the opinions of 12 experts . Data were collected using a researcher-developed questionnaire .The findings revealed that out of the 39 initial indicators, 11 were confirmed as the final components of audience-centricity in the arts, with three indicators—"investment in continuous learning and capability development," "adherence to privacy and data ethics," and "transparency in actions and communications"—attaining the highest level of importance. The alignment of the findings with the theoretical background not only confirms foundational theories such as market orientation and value co-creation but also demonstrates the study's innovation in introducing an "ethical-strategic framework" as the core of audience-centricity in the age of digital art.

Abstract The aim of the present study is to develop a performance evaluation management model for the internal supply chain using a hybrid DEMATEL and Analytic Network Process (ANP) approach. In terms of purpose, the research is applied, and regarding data collection, it is descriptive-survey in nature. The statistical population consisted of 12 experts, including 5 members from the hospital’s internal logistics unit and 7 managers from Namazi Hospital.To determine the relationships among the 13 indicators and 5 main components of the hospital’s internal supply chain, the DEMATEL method was employed. These relationships were then incorporated into the Analytic Network Process model, and the weights of the 13 indicators were determined using Super Decisions software.The 13 indicators were ranked respectively as follows: performance in completing patient treatment through access to complete treatment resources, delay-free patient treatment performance, patient waiting time, treatment service supply time, professional value-added efficiency, error-free performance in patient safety, continuity of the clinical treatment supply process, reliability and accessibility of treatment service suppliers, communication with patients, overall logistics cost management in the clinical treatment supply chain, reliability of investment and growth and revenue in the clinical treatment process, enhancement of hospital staff skills to prevent errors, and development of organizational culture.The findings indicated that the hospital’s internal supply chain has a positive, direct, and significant impact on hospital performance. The results of this study can be highly beneficial for optimal management, decision-making, and administrative practices in hospitals.

Abstract The purpose of this study is to develop a model for the typology of consumer behavior in response to packaging messages in the Iraqi market. In terms of research purpose, the study is developmental; in terms of data collection method, it is survey-based; and in terms of its nature, it is exploratory. The research was implemented using a quantitative approach and analyzed through Structural Equation Modeling (SEM).The statistical population consisted of managers, owners, marketing and production managers, as well as customers of these products in Iraq. Based on Cochran’s formula, a sample size of 476 respondents was determined and selected using simple random sampling. The primary data collection instrument was a structured questionnaire. Data analysis was conducted using SPSS version 27 and SmartPLS version 4.0.
The findings indicate that packaging color significantly influences environmental awareness, packaging retention, social influence, and packaging value selection. Furthermore, environmental awareness has a significant effect on social influence and packaging value selection. Packaging imagery positively affects packaging value selection, while packaging retention also contributes to packaging value selection.In addition, rapid information scanning significantly affects environmental awareness, packaging retention, social influence, and packaging value selection. Information-seeking behavior also influences packaging value selection, and social influence has a significant effect on packaging value selection.Overall, the results highlight the strategic role of packaging communication elements in shaping consumer perceptions and decision-making processes within the Iraqi market.

Abstract The aim of the present study is to develop a qualitative model of innovative modern banking services based on Customer Knowledge Management (CKM). In terms of purpose, the study is applied–developmental, and with respect to its methodological approach, it adopts a qualitative design using thematic analysis, consistent with its exploratory nature.To collect and select relevant scholarly literature, major academic databases including Scopus, Web of Science, and Google Scholar were utilized. In the initial stage, an extensive search across these databases resulted in the identification of 198 articles. Following a rigorous screening of titles, abstracts, and keywords, 32 eligible articles were selected for coding and qualitative analysis. The data analysis process was conducted using MAXQDA software through systematic coding procedures and theme extraction.The findings of the thematic analysis revealed that the qualitative model of innovative modern banking services grounded in Customer Knowledge Management is structured around five key components: (1) intelligent technological infrastructures and capabilities; (2) customer knowledge management processes; (3) innovation in the design and delivery of banking services; (4) value co-creation and knowledge-based customer interactions; and (5) environmental dynamics and institutional requirements of banking innovation.These components interact synergistically to provide an integrated framework for the development of banking service innovation. The proposed model offers a practical foundation for banking managers and decision-makers seeking to enhance customer experience, strengthen competitive advantage, and achieve sustainable innovation.

Abstract The purpose of this research is analyzing and localizing brand authenticity components in the healthcare industry. Aiming to propose a localized model, this study first identified 15 primary brand authenticity factors through a systematic literature review and qualitative content analysis utilizing NVIVO software. Subsequently, these factors were localized for the Iranian healthcare context through the Delphi method involving 12 academic and industry experts, resulting in 12 final validated factors, including transparency and honesty, strong brand legacy, existential originality, and brand sustainability and social responsibility. The findings indicate that the alignment between a healthcare organization's declared values and its actual performance serves as the fundamental basis for patients' perceptions of authenticity. By focusing on localized dimensions, this research offers a scientific framework for healthcare managers and policy makings to fundamentally transition from intuitive to evidence-based decision-making, thereby facilitating the strengthening of patients' networked trust and the enhancement of the therapeutic experience quality.

Abstract This study aimed to design an optimal symbiosis model of artificial intelligence and human capital in the delivery of urban services for the municipalities of Sistan and Baluchestan Province. The research was conducted in two phases: qualitative and quantitative. In the qualitative phase, document analysis, interviews, and the Delphi technique with the participation of 20 experts were employed to explore and develop the initial model. The software used in this phase was MAXQDA. In the quantitative phase, data were collected from 300 employees of the province's municipalities using a researcher-developed questionnaire, the validity and reliability of which were tested and confirmed, and subsequently analyzed through structural equation modeling. The findings indicated that the final research model enjoys a good fit and comprises six main constructs: contextual factors, AI components, human capital components, mediating factors, symbiosis strategies, and desirable outcomes. The strongest relationship in the model was observed between contextual factors and AI components, with a path coefficient of 0.98. This research offers a localized model for optimizing human-AI collaboration in the municipalities of underprivileged regions.

Abstract The present study aims to develop a grounded model of the social acceptance of smart home technology among Iraqi consumers. This research was conducted within the framework of an interpretive paradigm using a qualitative approach. The study population consisted of 15 experts in smart home technology and university scholars specializing in marketing, who were selected through the snowball sampling technique and participated in semi‑structured interviews.Data were collected through semi‑structured interviews and analyzed using the latent content analysis technique with MAXQDA 2024 software. The analysis process was carried out in three stages: open coding, axial coding, and selective coding.The findings led to the identification of several key categories, including smart home technology acceptance, perceived trust and security, lifestyle integration behaviors, economic decision‑making, and responses to social influence, from which seven main and novel hypotheses were derived. The results also indicate that the core category, “social acceptance of smart home technology,” represents a multidimensional construct influenced by cognitive, social, and innovative dimensions.

Abstract The aim of this study is to design a model for the implementation of a data‑driven human resource system using digital and intelligent tools. In terms of purpose, the study is fundamental, and in terms of methodology, it adopts a qualitative approach. The research population consisted of 15 experts and academic specialists, including university faculty members and managers of the Blood Transfusion Organization, who were selected through purposive and theoretical (judgmental) sampling. Data were collected through semi‑structured interviews. The collected data were analyzed using MAXQDA software.The results showed that through axial coding, 44 initial codes were organized into 22 axial codes, representing the key concepts and structural dimensions of a data‑driven human resource system. A comprehensive examination of the factors influencing the implementation of a data‑driven human resource system using digital and intelligent tools indicates that this process represents a multidimensional and strategic transformation that requires simultaneous attention to a set of causal factors (five dimensions), contextual factors (four dimensions), intervening conditions (four dimensions), strategies (four dimensions), and consequences (four dimensions).By presenting an integrated and data‑driven model, this study highlights the role of digital and intelligent tools in improving human resource processes and strategic decision‑making, and provides valuable theoretical and practical guidance for organizations pursuing digital transformation.

Abstract This applied-developmental study aimed to identify the dimensions and constitutive elements of a fintech-based service delivery model, anchored in a customer-centric approach within the Iranian banking sector. Utilizing a qualitative methodological framework, data were collected through a comprehensive literature review and semi-structured interviews with purposefully selected banking executives until theoretical saturation was achieved. The collected data were processed through thematic coding and analysis using MAXQDA 2020. The findings indicate that the proposed model comprises five core dimensions: Technological Infrastructure and Capabilities (digital infrastructure, emerging financial technologies, cybersecurity and privacy, and technological integration); Customer Centricity (customer insight, customer experience, service personalization, and customer engagement); Digital Financial Services (diversity of fintech services and innovative tools, digital service quality, service accessibility, and financial service innovation); Banking Structure and Management (digital transformation strategy, organizational innovation culture, social responsibility, and banking sustainability); and the Institutional and Regulatory Environment (fintech laws and regulations, supervision and regulation, and institutional support).

Abstract The aim of this study is to develop a framework for implementing demand-driven, AI-enabled business intelligence in the apparel industry. The study is applied in purpose and adopts a mixed-methods design (qualitative–quantitative). In the qualitative phase, 17 university faculty members, domain experts, sales specialists, apparel industry managers, and AI specialists were selected through purposive sampling. In the quantitative phase, 384 managers, senior experts, data analysts, supply chain managers, and information technology specialists in the apparel industry were recruited using cluster random sampling. Data were collected via semi-structured interviews and a questionnaire. Qualitative data were analyzed using MaxQDA 2020, while quantitative analyses were conducted with SPSS and PLS-SEM.The coding process generated 675 initial codes, which were refined to 461 codes after cleaning and subsequently organized into 214 conceptual codes, 45 subcategories, 19 main categories, and 6 core categories. Based on the paradigmatic model, key causal conditions included intensified competition, shifts in customer roles and market behavior, rising internal costs, and resource constraints. Continuous learning and monitoring, along with privacy protection, were identified as facilitating interventions; conversely, limited AI competencies, resistance to change, and legal constraints may function as inhibiting interventions. These conditions shape strategies such as transformational leadership, organizational memory management, and technology investment. Overall, the proposed model is aligned with firms’ internal and structural challenges.

Abstract This study aims to investigate the impact of Green Human Resource Management (GHRM) on green behavior, considering the mediating role of environmental awareness and the moderating role of managers’ green commitment within the food industries of Zahedan. In terms of purpose, the research is applied; in terms of execution, it is quantitative; and in its nature and method, it is descriptive-correlational. Data were collected using standardized questionnaires based on a 5-point Likert scale. Content validity was confirmed by experts, and reliability was assessed using Cronbach’s alpha and Composite Reliability (CR). Furthermore, construct validity was evaluated through three methods: structural validity (outer model), convergent validity (AVE), and discriminant validity. The AVE value for all variables was estimated to be greater than 0.5.Data analysis was performed using SPSS and SmartPLS 3 software. The results of Structural Equation Modeling (SEM) indicated that green human resource management, environmental awareness, and managers’ green commitment all play a significant role in reinforcing employees’ green behaviors and advancing the organization’s environmental goals. Additionally, environmental awareness as a mediator and managers’ commitment as a moderator facilitate and strengthen the path toward institutionalizing eco-friendly behaviors and adopting a sustainable professional lifestyle.

Abstract The aim of this study is to present a model for sustainable financial resource provision in Iranian sports federations. This research was conducted qualitatively using the grounded theory approach. The statistical population consisted of 17 experts in the field of sports management and the management of sports federations. A semi‑structured interview was used as the data collection tool. Grounded theory was employed for collecting and analyzing the data. Data analysis was carried out in three stages: open coding, axial coding, and selective coding. MAXQDA 24 software was used for data analysis.The findings indicated that sustainable financial resource provision in Iranian sports federations, as the core phenomenon, is influenced by factors such as dependency on government budgets, lack of stable financial resources, and pressure from regional and global competitions, all of which emerge within a context shaped by economic constraints, managerial weaknesses, and infrastructural challenges. Factors such as government policies, the role of media, and organizational capabilities moderate the intensity and direction of these efforts. To overcome these challenges, strategies such as diversifying financial resources, commercializing sports, and strengthening federation branding are essential. Successful implementation of these strategies leads to outcomes such as financial independence, infrastructure development, and enhanced competitiveness of sports federations, ultimately ensuring the sustainable growth of sports in the country.