فصلنامه مدیریت بازرگانی
سال شانزدهم شماره 62 (زمستان 1402)

This study aims to identify and analyze the role of digital platforms in improving business processes, data management, and communications. It thoroughly examines the direct and indirect impacts of digital platforms on organizational structures and business performance to find how digital technologies can facilitate innovation and contribute to the development of new business models development. It also seeks to explore the challenges and opportunities they present for organizations. Focusing on a specific digital framework, this study investigates how digital platforms are utilized at different organizational levels to enhance productivity and efficiency in work processes. Additionally, it tries to comprehend how organizations can benefit from the innovative opportunities created by advancements in digital technology, emphasizing how these opportunities can be leveraged to improve customer interactions and marketing strategies.
 
This research employs the Delphi method to identify and analyze key drivers. The Delphi method is a systematic technique used to collect and align expert opinions through multiple rounds of questionnaires without direct interaction among participants. This approach enables the researcher to gather comprehensive data from various experts and perform deeper, more impartial analyses. Additionally, the study uses the MIC-MAC analytical software to assess the influence and interdependencies among the identified drivers. MIC-MAC is a powerful tool for mapping interactions and determining the level of influence and dependency between various elements in a system. By the use of this technique, the research provides a dynamic map of the drivers, helping to pinpoint key areas for intervention and optimization. Furthermore, the study employs trend analysis and intuitive forecasting methods to gain a deeper understanding of future trends and uncertainties. This part of the research focuses on environmental and economic changes that could significantly affect businesses. Through intuitive analysis, the study aims to predict complex market shifts and business environments that influence strategic decision-making in organizations.
 
The findings of this study highlight the pivotal role of digital platforms in accessing big data and conducting intelligent data analyses. These platforms enable organizations to process raw data more effectively and leverage advanced techniques such as machine learning and artificial intelligence to extract actionable insights. This process, in turn, promotes the development of sustainable and innovative business models that improve efficiency and profitability. Additionally, adaptability and flexibility in responding to digital technological changes are recognized as crucial factors for leveraging innovative opportunities. Organizations that can swiftly adopt and implement new technologies can compete effectively in the market and maintain their leadership positions. This flexibility helps organizations stay competitive and enhances their ability to respond to evolving customer needs and expectations. The findings also indicate that the integration of digital technologies with business strategies can drive the development of innovative products and services tailored specifically to meet customer satisfaction.
 
This research highlights the significance of developing digital capabilities and creating resilient, flexible business models in the digital age. The results demonstrate that to achieve success in the modern business landscape, organizations must implement strategies that not only enable them to respond swiftly to technological changes but also empower them to leverage these changes to create sustainable competitive advantages. This study can provide guidance for decision-makers and business managers on optimizing operations and enhancing internal efficiency through big data and intelligent analysis. Effective use of advanced technologies can help organizations gain new insights into their target markets and identify business opportunities that previously seemed unattainable. Additionally, it highlights the need for continuous education and development of human resources to ensure that employees can adapt to and effectively utilize new technologies. This requires fostering a culture that encourages innovation and continuous learning at all organizational levels, enabling employees to grow in a stimulating and supportive environment.

The sharing economy represents a new business model in which individuals share their assets with others. In other words, the sharing economy enables people to grant access to their possessions for others' use. In some cases, this access is temporary and may even serve as a means of selling products and services. Typically, this sharing of assets by consumers occurs through online platforms. Given the rapid growth of sharing economy businesses, trust has emerged as the most critical issue faced by companies operating in this sector. These businesses require extensive trust-based relationships between users and service providers. However, most individuals in these businesses are unfamiliar with one another, which presents challenges for sharing economy enterprises. Accordingly, this study aims to identify the antecedents of trust in the sharing economy.

This research was conducted using an exploratory mixed-method approach in two stages. The first step involved identifying the topic and determining the research problem as part of the qualitative content analysis process. The second step focused on sample selection. A systematic review method was employed to select the articles. Initially, the research question, “What are the antecedents of trust in the sharing economy?” was formulated. In the next stage, articles were searched across scientific journals and various databases, such as ScienceDirect, Emerald, Scopus, and Google Scholar, from 2014 to 2023. This search utilized keywords such as "trust," "sharing economy," and "trust in the sharing economy," resulting in the collection of 730 articles. After reviewing the articles, 438 were excluded based on their titles, 192 based on their abstracts, and 40 based on their full text and content, leaving 60 articles from reputable scientific journals and international conferences for analysis. It is noteworthy that the search and selection of articles continued until it was confirmed that adding more articles would not yield any new antecedents of trust in the sharing economy. After the article selection, the process of qualitative content analysis commenced. In this stage, after selecting words and sentences as meaning units, each article was reviewed twice by the researchers. Once the antecedents were identified, codes with similar concepts were grouped under specific sub-category names to form sub-categories. Sub-categories with common concepts were then grouped and labeled as main categories. Regarding the validity of the categorization, a coding and categorization guide was developed and reviewed by two subject-matter experts. After receiving their feedback, necessary revisions were made. In the second stage, the Best-Worst Method (BWM), a multi-criteria decision-making method, was used to prioritize the categories. Accordingly, a Best-Worst questionnaire was prepared and sent to 10 experts in the field of the sharing economy, selected through the snowball sampling method. Finally, the data from the Best-Worst questionnaire were analyzed using Excel software.

After a thorough examination, 26 indicators were identified as antecedents of trust in the sharing economy. These 26 antecedents were then grouped into six main categories. The identified categories include platform value propositions (social values, cultural values), brand experience (user experience, service personalization), consumers' ethical perceptions (platform security, user protection, transparency), perceived quality (service quality), platform branding (brand personality, brand strength), and platform capabilities (technical capabilities, reliability).

The results of the analysis indicate that platform branding is the most important category among the identified antecedents of trust in the sharing economy. In contrast, consumers' ethical perceptions were found to be the least significant category. After discussing the research limitations and offering suggestions for future research, practical recommendations were provided for businesses operating in the sharing economy sector.

In today’s knowledge-based economy, small and medium-sized knowledge-based companies play a crucial role in the economic and social development of countries. Governments, therefore, strive to provide the necessary support to foster the growth of such companies. However, one of the key challenges is the high level of competition in this sector. Hence, this study aims to present a social marketing model to help knowledge-based companies achieve a sustainable competitive advantage.

This research is applied-developmental in terms of purpose, descriptive in terms of data collection, and mixed-method in terms of data nature. The qualitative study population includes managers of knowledge-based companies selected through purposive sampling, with theoretical saturation reached after interviewing 17 individuals. The quantitative population consists of managers and experts from knowledge-based companies, with a sample size of 113 determined using Cohen's power analysis rule and G*Power software. Cluster-random sampling was used to select the participants. Data collection tools included semi-structured interviews for the qualitative part and a researcher-made questionnaire for the quantitative part. Thematic analysis was used for analyzing the qualitative interviews, while quantitative data were analyzed using the partial least squares (PLS) method. Data analysis was conducted using MaxQDA and SMART PLS software. The reliability of the qualitative section was assessed using Holsti’s method (observed agreement percentage), yielding a coder agreement of 0.633, which is greater than 0.6, confirming sufficient reliability for the qualitative analysis. The content validity of the questionnaire was confirmed through expert opinions. Additionally, Cronbach's alpha for the questionnaire was 0.816 in a preliminary study. After distributing the questionnaire, its validity was further assessed using three methods construct validity (outer model), convergent validity (AVE), and discriminant validity. The AVE values for all variables exceeded 0.5. Reliability was also confirmed with composite reliability (CR) and Cronbach’s alpha for each factor being greater than 0.7.

In the open coding phase, 283 codes were identified. Ultimately, through axial coding, five overarching themes, 11 organizing themes, and 51 basic themes were derived.

The results indicate that the social marketing mix, customer orientation, and marketing influence the legal and ethical responsibilities of the company. Legal and ethical responsibility, in turn, shapes the social marketing strategy, which impacts the company's economic, social, and environmental performance. It is expected that the sustainable performance of knowledge-based companies will lead to a competitive advantage in this sector. In this study, the GOF index was 0.616, which is greater than 0.36. Additionally, the RMS_theta index was 0.101, lower than 0.12. The SRMR index was calculated at 0.05, which is below 0.08, indicating a well-fitting model.

As digital advancements continue to evolve and grow, customers anticipate a smooth purchasing experience when they engage with businesses. To meet these expectations, businesses adopt an omnichannel marketing strategy, which offers customers a complete and uninterrupted purchasing experience, from initial contact to the end of the transaction. Recognizing the significance of this topic, a qualitative framework for implementing omnichannel marketing was developed through this study.Omnichannel marketing is becoming increasingly vital for businesses, as it enables them to create a consistent and personalized experience for customers across various channels and devices, thereby enhancing customer satisfaction, loyalty, and overall business performance.

The research employed Sandelowski and Barroso's seven-step model and the meta-synthesis approach. A total of 590 articles on omnichannel marketing were identified by searching reliable national and international scientific databases. After screening the title, abstract, and results, and carrying out an in-depth examination of the chosen articles using the CASP method, 89 key articles were selected for further analysis. The analysis was conducted using MAXQDA software by coding the articles.

The study's results revealed a comprehensive framework, including 1,087 open codes, 90 first-level subcategories, 13 second-level subcategories, and a three-tier model comprising four primary categories for implementing omnichannel marketing.

According to the study's findings, the implementation of omnichannel marketing relies on four key concepts, which are processes and functions, environment, customer interaction, as well as resources and capital. Additionally, out of the 13 subcategories at the second level, nine were given priority due to their high repetition in the data analyzed. These subcategories include organizational strategy and structure, market, business environmental background, customer behavioral characteristics, technology resources, customer characteristics, financial resource management, human capital, and human resource management. Finally, the study revealed 22 high-priority subcategories at the second level that businesses and marketers can leverage to effectively implement omnichannel marketing strategies. By focusing on the four main categories of processes and operations, environment, customer engagement, and resources and capital, businesses can build a strong foundation for their omnichannel marketing efforts. Two types of research are recommended for future investigation. First, to quantify the qualitative findings, one could prioritize the main categories, first-level subcategories, and second-level subcategories using various techniques and the insights of both Iranian and international experts. This research could be further categorized by industry, such as retail or banking, where omnichannel marketing is particularly relevant. Second, the proposed framework could be employed to assess and rank the antecedents of omnichannel marketing within Iranian organizations. This would enable them to identify their strengths and weaknesses, thereby better positioning themselves to achieve global standards in omnichannel marketing.

Projections on the severity of climate change-related disruptions and displacements are becoming increasingly alarming over time (DiBella, 2020). Since climate change-related hazards have large impacts on a vast range of businesses, from individual traders to multinational companies (Canevari-Luzardo, 2020; Goldstein et al., 2019; Neise et al., 2018; Schneider, 2014; Surminski, 2013; Surminski et al., 2018), direct and indirect losses (e.g., damage to personnel, assets, and stocks) have been inflicted on businesses. Therefore, in environments where climate change has led to environmental uncertainty, it seems necessary for organizations to create new marketing strategies and capabilities to address this issue. However, considering the consequences of climate change, no research has yet identified the dynamic marketing capabilities based on climate change. On the other hand, past research has focused on B2B marketing capabilities in developed countries such as the United States (Mariadoss et al., 2011; Krush et al., 2015), the United Kingdom (Kaleka & Morgan, 2019; Yu et al., 2014), Australia (Merrilees et al., 2011; O'Cass & Weerawardena, 2010), and Germany (Helm et al., 2020; Wilden et al., 2019). As a result, the findings of these studies cannot be generalized to developing countries (Kamboj & Rahman, 2015; Mora Cortez & Johnston, 2018), where there are some of the most serious vulnerabilities to climate change (Odell et al., 2018). Additionally, since marketing is a contextual discipline (Sheth, 2011), the required marketing capabilities that drive firms' long-term performance can vary across countries and industries (Mora Cortez & Johnston, 2018). This is particularly relevant in Iran, which is one of the countries facing unprecedented problems related to climate change, including the drying up of lakes and rivers, dust storms, unprecedented temperatures, droughts, and floods (Vaghefi et al., 2019). Therefore, this research was conducted to fill these research gaps and to answer the question: "What is the conceptual framework of dynamic marketing capabilities driven by climate change?"
 
To provide a conceptual framework of dynamic B2B marketing capabilities based on climate change, a thematic analysis method, which is a qualitative method for organizing and describing existing data by identifying underlying themes, was used to analyze the data (Braun & Clarke, 2006). This approach was chosen because qualitative research findings provide a rich and accurate picture of the studied phenomenon. Among the different methods of data collection in this research, the semi-structured interview method was used online via a webcam.
 
In this section, the analysis process of the data obtained from the interviews was examined based on the three-step method of thematic analysis. This research outlined the framework of dynamic marketing capabilities driven by climate change, identifying 109 basic codes and 8 sub-themes, which are categorized into 3 main themes: product development management, supply chain management, and customer relationship management based on climate change.
 
Since climate change has caused many transformations and natural disasters, such as floods, droughts, fires, and storms, businesses that view climate change only as a social responsibility are doomed to failure. The consequences of climate change lead to many disruptions and problems for businesses. The results of this research indicate that addressing climate change requires both significant and minor changes. Businesses that engage with climate change must provide a roadmap for change because their survival depends on managers' attention to the risks and opportunities presented by climate change. Therefore, it is essential for businesses to develop new marketing capabilities based on climate change to mitigate the effects of risks and capitalize on the productivity opportunities arising from climate change.

In recent years, various approaches have been used to implement marketing activities and achieve companies' sales goals. One of the most widely adopted strategies is using different discount formats. A key challenge for companies is the effective utilization of product-appropriate discount formats. The lack of coherent knowledge about the types of discount formats and their impact on sales motivates this research. This study employed a mixed-methods approach and was conducted in two consecutive phases: qualitative and quantitative. One of the key issues in price discounts is framing them correctly and using appropriate formats that align with the product and discount conditions to maximize their effectiveness. Therefore, it is crucial to provide a comprehensive list of discount format types and consult sales experts to assess their effectiveness.
 
A mixed-methods approach was used, and the research was conducted in two consecutive phases. The first stage was carried out by systematically reviewing studies carried out in the last 10 years and using the three-step process of Turnfield et al. (2003), through which 87 articles were selected and analyzed. Then, the typology method was used for classification. To implement the typology stage, discount formats in the articles were coded using MAXQDA software, and a total of 55 codes for various discount formats were identified. This comprehensive list of discount codes is essential for the next step of researching and ranking discount formats. The codes of various discount formats were classified in a matrix based on the opinions of professors and experts, and the typology of discount formats was performed. The logic of the typology is based on whether the discount is cash or non-cash and the type of discount dependency (depending on the time of purchase, type of product, etc.). In the second stage, a quantitative study was conducted with a community of sales experts, and data was collected through a questionnaire. The discount formats identified in the first step were ranked, and the most effective discount formats on the company’s profit were identified, using the fuzzy TOPSIS method. Theoretical validity was assessed by gathering experts' opinions through theoretical pluralism. Quality was also evaluated by assessing reliability. To determine reliability, a doctoral student in Business Administration with a background in coding was invited to participate and we used the intra-subject agreement method of two coders (repeatability index), which was deemed acceptable with a reliability percentage above 60%. Moreover, the reliability of the codings was determined, and it can be claimed that the reliability of the articles’ analysis is acceptable through the systematic review. Of the 87 reviewed articles, 344 codes were extracted, of which 55 were non-repeated. The researchers asked the coding colleague to code 5 articles, and the results are presented in a table showing the reliability percentage. In the second phase, using the fuzzy TOPSIS technique, the decision matrix is purely a mathematical matrix through which the options are evaluated against the criteria. Therefore, the conceptual variable is not measured by criteria like statistical questionnaires, but only the score of each option in each criterion is determined by an expert. It does not represent a statistical questionnaire. Hence, since it is not a questionnaire, the validity and reliability do not apply to the decision matrix.
 
Based on the data analysis, in the first phase, the identified discount formats were classified into six categories, and in the second phase, the ranking list of ten selected formats was obtained. In the second stage of the research, after analyzing the data, managers and business experts were consulted to determine how and in what order they prioritized discount formats based on their impact on the company's profit. The results revealed the following prioritization: 1) Cash discount, 2) Percent discount, 3) Volumetric discount, 4) Event discount, and 5) Discount on customer performance.
 
If companies wish to implement discount programs in sales, they must first evaluate the suitable discount formats and then select the most appropriate one with careful consideration. Managing discounts by considering factors such as discount type, threshold, and timing can help prevent profit leakage and maximize the value provided by the firm

As a key service sector, Iran's banking industry has encountered numerous challenges and difficulties in past years. One potential solution is embracing innovation, particularly ambidextrous innovation. Accordingly, this research aims to identify the factors influencing the development and implementation of ambidextrous innovation within Iran’s banking sector and to prioritize them using a structural-interpretive model (ISM).
 
This research adopts a pragmatist paradigm and utilizes a hybrid approach that integrates practical objectives with diverse data collection methods. It studies Iran's banking industry, focusing on a statistical population comprising experts, university professors, senior bank managers, and specialists in innovation, technology, digital transformation, and process re-engineering. These individuals possess significant knowledge, expertise, and responsibility in the domains of strategy, decision-making, and the implementation of innovation in banks. The research utilizes a judgmental sampling method. This study was conducted in two stages: qualitative and quantitative. In the qualitative stage, content analysis was employed. The study began with a review of the existing literature on ambidextrous innovation, followed by interviews with 24 experts from the banking sector. These interviews helped identify the key factors influencing the development and implementation of ambidextrous innovation in the industry. In the quantitative phase, a questionnaire was distributed among 13 experts. The data collected was used to develop a self-interaction matrix and to proceed through the stages of structural-interpretive modeling (ISM). Ultimately, the factors identified in the qualitative stage were prioritized and presented in a structured model.
 
Based on the findings of this research, the qualitative section identified 67 components, 15 concepts, and 6 main categories that influence the creation and implementation of ambidextrous innovation in the banking industry. The six main categories are the executive process mechanism, organizational learning, the role of leadership style in innovation, the development of technological infrastructure, organizational foundation, and understanding the turbulence of the competitive environment. In the quantitative section, these factors were classified into three levels. The first level included the executive process mechanism, organizational learning, and the creation of technological infrastructure. The second level embraced the role of leadership style in innovation, and the third level comprised the organizational foundation and understanding of the turbulence of the competitive environment. Ultimately, the final research model was developed based on these classifications.
 
Based on the findings, banking industry managers should prioritize strengthening the organizational foundation and enhancing their understanding of environmental turbulence, as these factors have the most significant influence and are least affected by other variables. In the next phase, they should focus on fostering innovative and collaborative leadership styles to facilitate the creation and implementation of ambidextrous innovation. Finally, managers need to develop technological infrastructures, emphasize organizational learning, and implement knowledge management practices within banks, ensuring that the execution of ambidextrous innovation becomes operational. The findings suggest that adopting ambidextrous innovation—balancing exploratory and exploitative approaches—can transform Iran's banking industry into a more dynamic sector. Ambidextrous innovation can enable banks to overcome organizational stagnation and employee disengagement, fostering the development of diverse financial products that effectively meet customer needs. Furthermore, the research indicates that the creation and implementation of ambidextrous innovation can enhance the performance of Iran’s banking and financial ecosystem. One potential outcome is the formation of networks and alliances among different elements of the banking ecosystem, facilitating financing for the value chains of businesses. This highlights the significant role of ambidextrous innovation in reshaping Iran's banking system.

The widespread occurrence of fraud in chain stores poses a major challenge for the retail sector. The issue can be examined from multiple perspectives: customer fraud during purchases, employee fraud, fraud against investors and stockholders by stores, and deceptive practices that stores use against their customers. There is a notable research gap regarding the latter type of fraud, which this study aims to address by exploring and identifying prevalent methods of customer deception in chain stores. This article aims to present a model for explaining the methods of deceiving customers in chain stores.
 
A mixed-methods approach was employed to illustrate the facets of customer fraud and deception by chain stores. Following a comprehensive literature review, in-depth interviews were conducted with (frequently purchasing) customers, industry experts, and key informants and professionals in the retail industry. This led to the identification of significant factors associated with customer deception in chain stores. Subsequently, a conceptual framework for the customer deception model was developed using cognitive mapping techniques, in collaboration with retail industry scholars and specialists. To validate the initial model, a quantitative field survey was conducted using structural equation modeling. This process led to the development of the final model, termed the "Customer Deception Tree".
 
Over half of the participants reported experiencing instances of fraud and deception, highlighting a critical concern for the retail industry. The identified components of customer fraud are visualized in a tree model format. This model outlines the prevalent methods of deceiving customers across five primary stems, which include misleading advertisements, failure to deliver promised services, price manipulation, alterations in product characteristics, and misplaced goods on shelves.
 
The act of misleading consumers by chain stores has emerged as a significant and increasingly pervasive unethical behavior in recent years. This research delves into the various dimensions of this issue, identifying and presenting contributing factors within a comprehensive model. This model serves as a guiding framework for stakeholders in the retail industry, including marketers and policymakers, particularly those involved in decision-making and strategic planning within chain stores, to address and mitigate this issue effectively. It is imperative to recognize the significance of avoiding such deceptive practices. Furthermore, the model can assist regulatory bodies and governance institutions in improving their protocols and supervision mechanisms, updating their enforcement strategies against fraud, and ensuring the protection of consumer rights. The tree symbol serves as a visual metaphor for the phenomenon of deception, aiming to alert consumers, the public, academics, and the research community to its existence. Ignoring or neglecting this symbol allows deceptive practices to grow and become more deeply rooted and widespread. By raising awareness of this "deceptive tree," there is an expectation that regulators will be encouraged to intervene, curbing its growth and influence by addressing deceptive tactics before they become even more ingrained.

Collaboration between industry and academia is a significant and intriguing topic within Iran's academic and industrial spheres. A key reason for its importance lies in the potential for industries to leverage the scientific expertise and resources of universities. However, an important question is whether such relations can have a positive impact on the attitude of Iranian consumers, regarding the company's manufactured products. The current research aims to answer this question. Manufacturing companies use different strategies to enhance the appeal of their products from the perspective of end consumers. Using new technology, high-quality raw materials, advertising, appropriate pricing, and appropriate distribution are some of the strategies used by companies to attract consumers. In the meantime, the cooperation between the manufacturing company and the university in the production of the final product has been rarely considered. Considering the high potential for industry-university cooperation, this research investigates whether the cooperation of a manufacturing company with a university influences purchase attractiveness, including product preference, purchase intent, and willingness to pay among Iranian consumers.

This research is practical in terms of purpose and experimental in terms of the method of implementation. The statistical population of this research includes Iranian consumers. To examine the cause-and-effect relationship, the impact of a company's collaboration with a university on the attractiveness of its manufactured products was analyzed using an experimental approach. For this purpose, five experimental studies were conducted.

The findings of this research show that the cooperation of the manufacturing company with a university in product development enhances product attractiveness, resulting in increased product preference, purchase intent, and willingness to pay among Iranian consumers. This impact was confirmed for startups and established companies. Results confirm the mediating role of consumers’ trust in the company's product in the aforementioned relationship. The reason why the products produced in collaboration with the university are more attractive is that such products are more trustworthy in the eyes of Iranian consumers.

The findings of this research indicate that Iranian consumers hold a positive perspective on industry-university collaboration in the production of manufactured products. Therefore, manufacturing companies are not only encouraged to collaborate with universities in the development of new products but also to effectively communicate this collaboration to potential consumers. It is suggested that the manufacturing companies emphasize this cooperation in the communication and advertising programs of the products they have produced in collaboration with the university. While this study examined the causal relationship in several scenarios, using an experimental method, further research is recommended to generalize the findings to other contexts, particularly the service sector.

This study aims to identify the antecedents of brand archetypes through a cross-sectional analysis conducted in Hamedan, a city in western Iran, between 2020 and 2021.
 
This research is both fundamental and applied in its objectives, qualitative in nature, and field-based in its execution. Data was collected through semi-structured, in-depth interviews with open-ended questions, accompanied by note-taking. Given that the research is survey-based with non-probability, purposive sampling, the target population for each brand was determined separately. The samples were selected intentionally based on specific characteristics known to the researcher beforehand, ensuring they would contribute meaningfully to the research objectives. Interviews were conducted with brand owners, managers of well-known brands, and marketing professors. A phenomenological approach and coding using Maxqda software were employed to extract features that serve as antecedents of brand archetypes. Based on these features, the archetype for each brand was determined.
 
The study involved 137 interviews across 12 selected brands. Coding these interviews using Maxqda generated 2,316 codes, consisting of 457 sub-codes, 79 semi-sub-codes, and 12 main codes. From these interviews, specific features were identified as antecedents to each brand's archetype. The findings reveal the following archetypes for the respective brands: Apple as the Creator, Xbox as the Magician, Pepsi as the Jester, Jeep as the Explorer, Diesel as the Outlaw, Rolex as the Ruler, Sony as the Sage, Chanel as the Lover, Coca-Cola as the Innocent, Gap as the Everyman, Nike as the Hero, and Niva as the Caregiver.
 
The results of this study suggest that archetypes help in understanding the meaning and concept of a brand, serving as crucial tools for marketing and branding, and distinguishing brands from one another. A brand’s personality is a significant factor in attracting customers. It is the brand’s personality that shapes how customers feel about the brand. Each brand, through its archetypes, connects with customers who have similar personalities. For a brand to succeed in the market, it must establish a deep and meaningful connection with its customers. This connection fosters a sense of loyalty and trust, ultimately attracting customers to the brand and creating customer satisfaction. One of the most effective strategies for building a strong emotional bond between a brand and its customers is to design the brand’s personality around archetypes. This approach deeply influences the customer’s perceptions and emotions, transforming ordinary buyers into loyal, lifelong patrons. The brand’s personality determines how customers feel about it. Brands must connect deeply and meaningfully with their customers, and the best way to achieve this is by designing their personalities based on archetypes. Additionally, the findings of this study can be leveraged to develop effective marketing and branding strategies that build a brand’s identity by utilizing the antecedents of brand archetypes.

In recent years, the emergence of concepts such as customer value creation, organizational networks, and open innovation has elevated open business models as an innovative approach in management studies. These models have garnered significant attention in both academic and practical arenas due to their foundational emphasis on collaboration among organizations. However, comprehensive research on specific business models and their maturity stages within the Iranian banking sector remains sparse. This article seeks to develop a model for the maturity of business model openness in this industry. Its primary goal is to identify the distinguishing factors between open and closed business models and to examine the maturity stages and their respective characteristics.

This study was conducted in two distinct phases. In the first phase, a systematic review of 303 relevant studies was performed, leading to an in-depth analysis of 30 selected articles. This phase facilitated the identification and categorization of key factors influencing business model openness. The systematic review approach ensured that a comprehensive range of literature was considered, allowing for a robust understanding of the current state of knowledge in this area. In the second phase, a grounded theory approach was employed to gather essential data through interviews with 14 experts from the banking industry. These experts provided valuable insights into the practical implications of business model openness. This methodological framework significantly contributed to the formulation of the maturity model for business model openness in this sector.

The research identified 13 subcategories and 48 codes that delineate the distinguishing factors between open and closed business models. These factors were organized into four main categories: deliverable value, value creation, value capture, and value networks, each comprising specific subcategories and codes. This structured classification allows a clearer understanding of how different elements interact within business models. Additionally, the study introduced a classification of business models in the Iranian banking industry from a developmental perspective, providing insights into how these models evolve. This classification offers strategies for enhancing organizational performance and adapting to changing market conditions.

This research's findings present a comprehensive model for identifying the distinguishing factors of business models from the perspective of openness within the Iranian banking industry. The maturity framework elaborates on the stages of business model openness and the specific characteristics inherent to each stage. Furthermore, this research serves as a case study that can inform strategies to enhance business practices and boost the competitiveness of banks, facilitating transformative changes within the industry. Ultimately, this research addresses critical scientific and practical gaps in the literature surrounding open management and innovation in the banking sector. It stands as a reliable resource for industry experts and managers, emphasizing the growing significance of business model openness in today’s dynamic environment. The results of this study can guide organizations in their efforts to evolve and optimize their operational performance, ensuring they remain competitive in an increasingly interconnected world.