Bayesian Estimation Black-Litterman Case Solution

The Harvard Business Review published a case study that primarily focuses on Bayesian Estimation Black-Litterman. The following case solution has been designed to give the reader an overview about the business world along with a clear understanding of its growth dynamics. Recently, Bayesian Estimation Black-Litterman has been subjected to strategic as well as managerial problems that require immediate attention so that they can be resolved to allow future growth, expansion, and competitive edge within the marketplace. This case study solution is being written to provide a strategic solution to Bayesian Estimation Black-Litterman using various appropriate tools and frameworks. Harvard Business Review’s case studies involve a central problem that is faced by a particular company. The problem identified involves strategic and managerial implications for the company. Therefore, it is important for readers to critically identify the problem Bayesian Estimation Black-Litterman faces. Moreover, it is also essential to highlight the key stakeholders that are impacted and influenced by the problem identified.

External Environmental Analysis

The external environment holds significant importance for Bayesian Estimation Black-Litterman to ensure that the company is able to respond to all the changes in the macro-environment. This is because Bayesian Estimation Black-Litterman cannot control the factors and thus can directly influence the company's operations (Indris & Primiana, 2015). The external environment of Bayesian Estimation Black-Litterman will be assessed using PESTLE Analysis.

Political

• A stable political environment provides a favorable market growth trend for Bayesian Estimation Black-Litterman.

• It is important for Bayesian Estimation Black-Litterman to analyze the pressure groups, and social environment activists. The company can make close collaborations with these groups to achieve company goals (Wang, Wang, & Shi, 2022).

• High restrictions on trade and high levels of taxes can contribute to the complex business environment for Bayesian Estimation Black-Litterman by impacting imports and exports.

Economic

• Bayesian Estimation Black-Litterman can benefit from wide-range opportunities in business growth by operating in developing economies (Munro, 2017).

• High GDP can determine the long-term growth strategies of Bayesian Estimation Black-Litterman, signaling the ability of consumers to spend on more products.

• Higher rates of interests can provide Bayesian Estimation Black-Litterman with more investment opportunities.

• The flexibility in the labor market allows Bayesian Estimation Black-Litterman to take advantage of higher workforce productivity.

Social

• The selection of appropriate demographic segments has allowed Bayesian Estimation Black-Litterman to select the right segments of the market that have high growth potential.

• The research on gender roles has helped Bayesian Estimation Black-Litterman to develop and align communication as well as marketing strategies accordingly.

• Bayesian Estimation Black-Litterman has been successful in understanding the norms and cultures of different countries by developing local teams and partnerships (Hueske, Endrikat, & Guenther, 2015).

Technological

• The adoption of innovative marketing techniques that involves communication technologies has allowed Bayesian Estimation Black-Litterman to collaborate successfully with consumers.

• The company has stayed ahead in the market, and can significantly increase its market share by placing its major focus on emerging technologies (Akpoviroro & Owotutu, 2018).

• Bayesian Estimation Black-Litterman should maximize its profits by investing in disruptive technologies.

Environmental

• It is crucial for Bayesian Estimation Black-Litterman to adopt effective waste management practices to reduce environmental pollution (J. K, W. J, & D., 2016).

• Bayesian Estimation Black-Litterman should adopt eco-friendly products to establish better relationships with the stakeholders.

• Bayesian Estimation Black-Litterman can take advantage of subsidies offered in renewable technologies to achieve the long-term goal of sustainability.

Legal

• Bayesian Estimation Black-Litterman should follow proper laws concerning employee health and safety, and anti-discrimination laws to effectively develop HRM.

• Consumer protection laws are also important for Bayesian Estimation Black-Litterman as it involves the consumer protection from fraudulent marketing (S. Samusenko, S. Plaskova, & A. Prodanova, 2020).

• Bayesian Estimation Black-Litterman can gain a competitive advantage, and can position itself strongly in the market by protecting intellectual property laws.

Porter’s Five Forces Analysis

Threat of New Entrants

• It is difficult to achieve economies of scale in Bayesian Estimation Black-Litterman’s industry, making it a weaker force for new entrants.

• There are high capital requirements in the industry. This makes it difficult for new businesses to set up their companies, and compete against Bayesian Estimation Black-Litterman.

• The industry has a strong product differentiation, and heavy investment is needed for customer acquisition. Thus, Bayesian Estimation Black-Litterman can focus on innovation to differentiate itself from its competitors (H. Th. Bruijl, 2018).

• There are strict legal requirements to join the industry in which Bayesian Estimation Black-Litterman operates, making it difficult for new entrants to enter the market.

Bargaining Power of Suppliers

• The bargaining power of suppliers in the industry is weak.

• Bayesian Estimation Black-Litterman operates in an industry with a higher number of suppliers. This means that suppliers do not have much control over their prices.

• Standardized products that have low switching costs are provided by suppliers allowing buyers like Bayesian Estimation Black-Litterman to easily switch their suppliers (Fabbri & F.Klapper, 2016).

• Raw materials can be purchased at lower prices by Bayesian Estimation Black-Litterman. The company can also switch suppliers for more reasonable pricing.

• Bayesian Estimation Black-Litterman can benefit from a variety of suppliers as it can have multiple suppliers for its various geographical areas (Cho, Ke, & Han, 2019).

Bargaining Power of Buyers

• The bargaining power of buyers in the Bayesian Estimation Black-Litterman industry is weak.

• There is a high product differentiation in the industry, making it difficult for buyers to switch to alternative firms.

• Bayesian Estimation Black-Litterman can come with differentiated and innovative products to attract more buyers of the industry (Zhao, Zuo, & Wu, 2016).

• Buyers of this industry has low incomes. This means they prefer to purchase items at lower prices, making them more price sensitive. Organizations like Bayesian Estimation Black-Litterman can offer lower prices to attract customers.

Threat of Substitute Products or Services

• There are few substitute products available in the industry in which Bayesian Estimation Black-Litterman operates.

• Expensive substitutes are available in the industry of Bayesian Estimation Black-Litterman, making it difficult for buyers to switch to those substitutes (Aithal, 2016).

Rivalry Among Existing Firms

• The rivalry among existing firms is moderate to weak.

• There are few competitors in the industry in which Bayesian Estimation Black-Litterman operates.

• A large market share is enjoyed by fewer firms in the industry. This means that more competitive actions will be made to become leaders in the market (Seema, 2016).

• The industry in which Bayesian Estimation Black-Litterman operates has highly differentiated products, making it difficult for companies to win each other customers.

• Bayesian Estimation Black-Litterman can focus on making more differentiated products to gain a strong competitive edge in the market (Zhao, Zuo, & Wu, 2016).

Internal Environmental Analysis

Bayesian Estimation Black-Litterman can use internal environmental analysis to identify and evaluate the competitive positioning of a company in the business environment. This involves conducting a SWOT Analysis that can help Bayesian Estimation Black-Litterman to identify the company’s internal strengths, weaknesses, opportunities, and threats (Halmaghi, Iancue, & Băcilă, 2017).

SWOT Analysis

Strengths

• Bayesian Estimation Black-Litterman has a strong distribution network that has allowed it to make its products available to large customers within the given timeframe.

• A strong presence on social media platforms has allowed Bayesian Estimation Black-Litterman to have a high level of customer engagement (Rizaldi, 2015).

• Bayesian Estimation Black-Litterman has been successful in building a large product portfolio, so unique and distinctive products can be offered to consumers.

• Bayesian Estimation Black-Litterman has a strong brand image in the market.

• A low-cost structure of Bayesian Estimation Black-Litterman has allowed it to manufacture products at lower costs, so they become affordable for consumers to purchase.

• The financial position of Bayesian Estimation Black-Litterman is strong as the company has generated higher profits over the past years (Phadermrod, M.Crowder, & B.Wills, 2019).

• Bayesian Estimation Black-Litterman has invested in the training and development of its employees to keep them motivates, leading to higher efficiency and productivity.

Weaknesses

• The expenditure of Bayesian Estimation Black-Litterman on its research and development is comparatively less to other competitors of the market.

• Bayesian Estimation Black-Litterman uses a centralized decision-making process that takes time and reduces operational efficiency (Ahmadi, Dileepan, & K. Wheatley, 2016).

• There are high rental costs because Bayesian Estimation Black-Litterman operates on more of the rental properties rather than purchasing them.

• There is no workforce diversification in Bayesian Estimation Black-Litterman. This makes it difficult for the employees to adjust with the different workers who belong to different backgrounds.

Opportunities

• Since the online shopping has increased significantly, Bayesian Estimation Black-Litterman can take it as an opportunity to expand its online presence.

• Bayesian Estimation Black-Litterman can make use of social media platforms to market its products, with more customers interactions.

• Due to more technological developments, Bayesian Estimation Black-Litterman can make its operations more automated so that overall company costs can be reduced (Ahmadi, Dileepan, & K. Wheatley, 2016).

• Globalization provides an opportunity to Bayesian Estimation Black-Litterman to expand its operations in multiple countries.

• Bayesian Estimation Black-Litterman can enter in a niche market and sell distinctive products to gain a competitive advantage.

• The increase in the demand of environmentally friendly goods, Bayesian Estimation Black-Litterman, can place its major focus on making such products (E.Quezada, A.Reinao, & I.Palominos, 2019).

Threats

• In recent times, there has been an increase in the bargaining power of suppliers, making it difficult for Bayesian Estimation Black-Litterman to buy raw materials at lower costs.

• Numerous players are entering the industry, posing a major threat to Bayesian Estimation Black-Litterman.

• There has been constant pressure on Bayesian Estimation Black-Litterman to conduct frequent research to understand the changing customer tastes and preferences (Kolbina, 2015).

• Technological advancements require workforce training. This adds to the costs of Bayesian Estimation Black-Litterman.

VRIO Analysis

Bayesian Estimation Black-Litterman uses VRIO Analysis to assess and evaluate the company resources to determine the competitiveness, and strategic advantage.

Valuable

• Bayesian Estimation Black-Litterman has a strong brand image and engages in corporate social responsibility.

• Bayesian Estimation Black-Litterman has a high brand recognition because of the quality of products it offers to its customers (Ariyani & Daryanto, 2018).

• The distribution system of Bayesian Estimation Black-Litterman is valued all round the world. The company has been able to successfully establish strong relationships with its suppliers.

• Bayesian Estimation Black-Litterman focuses on continuous innovation in its business. The company has expanded this innovation in its multiple functional areas.

• There are potential growth opportunities in the market, and Bayesian Estimation Black-Litterman has been able to penetrate the market through its ability to raise large funds.

Rare

• Bayesian Estimation Black-Litterman operates globally. This global presence has allowed the company to increase its customer base (Miethlich & G. Oldenburg, 2019).

• Bayesian Estimation Black-Litterman has an organizational culture that promotes more teamwork, innovation, and creativity among its employees, that leads to a competitive advantage.

• Since Bayesian Estimation Black-Litterman has a global presence, it allows the company to easily adapt to different cultures, norms and values.

• The risk-taking ability of Bayesian Estimation Black-Litterman is strong. This provides more opportunities to the company to penetrate different markets.

Inimitable

• The inimitable resource for Bayesian Estimation Black-Litterman is its high-quality products. These products have allowed consumers to make repeat purchases.

• Bayesian Estimation Black-Litterman operates through multiple locations of stores in different companies, allowing easy access to products.

• Strong marketing communications have been used by Bayesian Estimation Black-Litterman to attract more customers.

• Bayesian Estimation Black-Litterman has been using integrated technology that has allowed it to offer competitive pricing to its customers (Ariwibowo, Saputro, & Haryanto, 2021).

• Bayesian Estimation Black-Litterman maintains an excellent customer service that has enabled it to have a high brand engagement.

Organization

• Strong financial position has allowed Bayesian Estimation Black-Litterman to explore more product development opportunities.

• Bayesian Estimation Black-Litterman is successfully maintaining the efficiency and effectiveness of its business operations with the help of more integrated and advanced technology.

• Employees are given both in-house and off-the-job training opportunities by Bayesian Estimation Black-Litterman that allow more skills development (Adnan, Abdulhamid, & Sohail, 2018).

• The strong value chain and distribution network has enabled Bayesian Estimation Black-Litterman to increase its revenue through the sale of its products.

Marketing Mix

Marketing Mix is needed by Bayesian Estimation Black-Litterman to formulate effective strategies to achieve the company objectives.

Product

• Bayesian Estimation Black-Litterman has five product categories. Each of these categories has a product line that involves more variety of products (Išoraitė, 2016).

• Highly differentiated products are offered by Bayesian Estimation Black-Litterman to its customers. These distinctive products are not easily available at competitors.

• The products of Bayesian Estimation Black-Litterman are of higher quality, and thus, customers pay more prices for these products.

• Bayesian Estimation Black-Litterman designs products with traditional designs giving customers more product variety.

• Bayesian Estimation Black-Litterman offers multiple sizes for its every product to make it easy for its customers to select the right product.

• Warranty and same-day delivery option if also provided by Bayesian Estimation Black-Litterman to its customers.

Price

• Bayesian Estimation Black-Litterman follows a competitive pricing strategy.

• To attract more customers, bundle pricing has also been used by the company.

• Little higher prices are charged for products that are sold online because of the delivery costs (Thabit & Raewf, 2018).

• Optional product pricing strategy is also adopted by Bayesian Estimation Black-Litterman for some of its products, such as a base product is offered for a certain price, and there are separate prices for its accessories.

• Regular promotional prices are also offered by Bayesian Estimation Black-Litterman to its customers.

Place

• Bayesian Estimation Black-Litterman uses two channels for its product distribution. This includes online selling and through own stores.

• There are more than multiple stores owned by Bayesian Estimation Black-Litterman globally. This ensures easy product availability to customers (Pogorelova, Yakhneeva, & Agafonova, 2016).

• Bayesian Estimation Black-Litterman has partnered with delivery service companies to distribute its products effectively to consumers.

• Bayesian Estimation Black-Litterman has also adopted an omni-channel distribution system.

Promotion

• Bayesian Estimation Black-Litterman uses a traditional promotional strategy that involves TV advertisements (Fan, Y.K.Lau, & Zhao, 2015).

• Social media advertisements are also adopted by Bayesian Estimation Black-Litterman to increase brand awareness.

• Bayesian Estimation Black-Litterman takes part in various events and exhibitions as a way of promoting its products.

• Large sales force is used to provide the customers with a more personal experience.

• Bayesian Estimation Black-Litterman also makes use of influencer marketing to increase the demand for its products.

• Regular content and deals are posted on the social media pages of Bayesian Estimation Black-Litterman to attract and retain customers.

Value Chain Analysis

Bayesian Estimation Black-Litterman can use Value Chain Analysis to identify and assess inter-relationships as well as interdependencies.

Primary Activities

• Bayesian Estimation Black-Litterman’s primary activities involves the production and selling of products to the final consumers (Mintz, J.Gilbride, & Lenk, 2021).

• Bayesian Estimation Black-Litterman has a strong relationship with the suppliers. This ensures that the product is received, stored, and distributed in a timely manner.

• Operational activities of Bayesian Estimation Black-Litterman are effectively aligned.

• For inbound logistics, after the arrival of raw material, the company processes it to manufacture the final product (Hasan, Nekmahmud, & Yajuan, 2019).

• In terms of outbound logistics, Bayesian Estimation Black-Litterman has been able to set up optimal costs as well as efficient delivery processes to deliver the product on time.

• Bayesian Estimation Black-Litterman invests in its sales and marketing activities to build relationships with customers.

• Marketing funnel approach is used by Bayesian Estimation Black-Litterman to effectively devise and build sales and marketing activities.

• Bayesian Estimation Black-Litterman offers both pre-sale and post-sales services to its customers.

Secondary Activities

• Bayesian Estimation Black-Litterman has an effective infrastructure that has allowed the company to successfully optimize its value chain.

• The competitive pressure in terms of employee skill development, motivation, and commitment is reduced as Bayesian Estimation Black-Litterman has developed a strong HRM (Linkov, Carluccio, Pritchard, & Bhreasail, 2020).

• Bayesian Estimation Black-Litterman uses a cost minimization approach to reduce its costs by analyzing the costs associated with training and hiring the employees.

• Bayesian Estimation Black-Litterman has been using integrated technology in its value chain activities. This includes technological customer support, research and data analytics concerning product design, and automated software.

• The procurement activities of Bayesian Estimation Black-Litterman are effectively optimized with its inbound, outbound, and operational activities (Maheswari, Yudoko, & Adhiutama, 2019).

Market Penetration Strategies

• Bayesian Estimation Black-Litterman can increase the capacity of its production so it can reach more of the customers in its existing market.

• Bayesian Estimation Black-Litterman can focus on controlling the overhead costs so that it can offer competitive pricing that can attract customers of the market (Dawes, 2018).

• Investments can be made by Bayesian Estimation Black-Litterman in marketing and sales activities to increase the chances of successful market penetration.

• Bayesian Estimation Black-Litterman can design and develop a content that increases customer engagement within a particular marketplace.

• Bayesian Estimation Black-Litterman can assess and identify more enhanced distribution networks (Radpour, Mondal, & Kumar, 2017).

• Improved distribution systems and supply chains can improve the product accessibility for the customers, making it easier for Bayesian Estimation Black-Litterman to penetrate the market.

• Bayesian Estimation Black-Litterman can adopt price cuts in its products to compete in the market. This will give a company a competitive edge over its competitors.

• Bayesian Estimation Black-Litterman can plan strategies where it can focus on acquiring the leading players of the market. Such acquisitions will give the company an opportunity to reach more customer segments.

• Strategic partnerships and joint ventures agreements can be signed by Bayesian Estimation Black-Litterman to mitigate the risk factors, and to gain customer groups of the market.

• Bayesian Estimation Black-Litterman can come up with new and innovative features in its already existing product for the market (Daouda, Barth, & T. M. Ingenbleek, 2019).

Market Development Strategies

• It is important for Bayesian Estimation Black-Litterman to invest in the research and development department so potential markets can be identified (Hilman, Bohari, & Abdullah, 2018).

• Regional expansion strategy can be used by Bayesian Estimation Black-Litterman for growth purposes. This will also take into consideration the cultural differences.

• Bayesian Estimation Black-Litterman should also consider to expand its business operations in the international market. This will allow access to a larger customer base.

• New customer groups and segments should be explored by Bayesian Estimation Black-Litterman.

• Bayesian Estimation Black-Litterman should also invest in brand-building activities as it will give an opportunity to reach more potential customers (C. Koks & M. Kilika, 2016).

• Bayesian Estimation Black-Litterman should consider the market education in terms of its product. The company can significantly increase its sales by giving product awareness to new segments.

Product Development Strategies

• Bayesian Estimation Black-Litterman can come up with new improvements and modifications in the existing products to attract the market.

• Bayesian Estimation Black-Litterman should undergo the NPD process, so the company is able to assess and identify new points for its customers.

• Regular investments in the research and development will help Bayesian Estimation Black-Litterman to develop something new and innovative that can give a competitive advantage (Kalogiannidis & Mavratzas, 2020).

• Bayesian Estimation Black-Litterman can develop new products by getting into more strategic partnerships.

Diversification Strategies

• Bayesian Estimation Black-Litterman can adopt vertical diversification to develop business. This can be done by adding more products to the existing portfolio (Kalogiannidis & Mavratzas, 2020).

• Horizontal integration can also be adopted by Bayesian Estimation Black-Litterman, where the company can enter into a completely new product development phase that does not exist in the current product line.

• Bayesian Estimation Black-Litterman can also consider to conglomerate by starting a different business.

Conclusion

Based on all the models and frameworks discussed above, it is concluded that Bayesian Estimation Black-Litterman should focus on widening the existing product portfolio. Moreover, the psychological pricing strategy can be adopted. Bayesian Estimation Black-Litterman should also maintain close relationships with its suppliers to benefit from lower prices. Similarly, Bayesian Estimation Black-Litterman should develop more integrated outbound logistics for its perishable items. It is also important to continue producing quality and innovative products, so Bayesian Estimation Black-Litterman is less affected by the new emerging competition in the industry.

References

Adnan, M., Abdulhamid, T., & Sohail, B. (2018). Predicting Firm Performance through Resource Based Framework . European Journal of Business and Management .

Ahmadi, M., Dileepan, P., & K. Wheatley, K. (2016). A SWOT analysis of big data. Journal of Education for Business , 289-294 .

Aithal, P. S. (2016). Study on Bayesian Estimation Black-Litterman Analysis Technique for Business Models, Business Strategies, Operating Concepts & Business Systems. International Journal in Management and Social Science, 95-115.

Akpoviroro, K. S., & Owotutu, S. O. (2018). Impact of external business enviornment on organizational performance . International Journal of Advance Research and Innovative Ideas in Education, 498-505.

Ariwibowo, P., Saputro, F. B., & Haryanto, H. (2021). Analysis of Strength & Weakness, Using the Concept of Resource-Based View with the VRIO Framework in Sharia Cooperatives. Jurnal Manajemen Strategi Dan Aplikasi Bisnis, 279 - 294.

Ariyani, W., & Daryanto, A. (2018). Operationalization of Internal Analysis Using the VRIO Framework: Development of Scale for Resource and Capabilities Organization (Case Study: XYZ Company Animal Feed Business Unit). Asian Business Research Journal .

C. Koks, S., & M. Kilika, J. (2016). Towards a Theoretical Model Relating Product Development Strategy, Market Adoption and Firm Performance: A Research Agenda. Journal of Management and Strategy.

Cho, W., Ke, J.-y. F., & Han, C. (2019). An empirical examination of the use of bargaining power and its impacts on supply chain financial performance. Journal of Purchasing and Supply Management.

Daouda, F. B., Barth, P., & T. M. Ingenbleek, P. (2019). Market Development for African Endogenous Products. Journal of Macromarketing .

Dawes, J. (2018). The Ansoff Matrix: A Legendary Tool, But with Two Logical Problems. SSRN .

E.Quezada, L., A.Reinao, E., & I.Palominos, P. (2019). Measuring Performance Using SWOT Analysis and Balanced Scorecard. Procedia Manufacturing, 786-793.

Fabbri, D., & F.Klapper, L. (2016). Bargaining power and trade credit. Journal of Corporate Finance, 66-80.

Fan, S., Y.K.Lau, R., & Zhao, J. L. (2015). Demystifying Big Data Analytics for Business Intelligence Through the Lens of Marketing Mix. Big Data Research, 28-32.

H. Th. Bruijl, G. (2018). The Relevance of Porter's Five Forces in Today's Innovative and Changing Business Environment. SSRN .

Halmaghi, E. E., Iancue, D., & Băcilă, M. L. (2017). The Organization's Internal Environment and Its Importance in the Organization's Development. International Conference Knowledge Based Organization , 378 - 381.

Hasan, M. M., Nekmahmud, M., & Yajuan, L. (2019). Green business value chain: a systematic review. Sustainable Production and Consumption, 326-339.

Hilman, H., Bohari, A. M., & Abdullah, S. S. (2018). The mediating effect of cost leadership on the relationship between market penetration, market development, and firm performance. Journal of Business and Retail Management Research.

Hueske, A. K., Endrikat, J., & Guenther, E. (2015). External environment, the innovating organization, and its individuals: A multilevel model for identifying innovation barriers accounting for social uncertainties. Journal of Engineering and Technology Management, 45-70.

Indris, S., & Primiana, I. (2015). Internal And External Environment Analysis On The Performance Of Small And Medium Industries (Smes) In Indonesia. International Journal of Scientific & Technology Research .

Išoraitė, M. (2016). Marketing Mix Theoretical Aspects . International Journal of Research-Granthaalayah.

J. K, N., W. J, O., & D., K. (2016). Does External Environment Influence Organizational Performance? The Case of Kenyan State Corporations. Management and Organizational Studies.

Kalogiannidis, S., & Mavratzas, S. (2020). Impact of marketing mix strategies effective product development issues in MNCs/Retail . International Journal of Business Marketing and Management , 118-125.

Kolbina, O. (2015). SWOT Analysis as a Strategic Planning Tool for Companies in the Food Industry. Problems of Economic Transition, 74-83 .

Linkov, I., Carluccio, S., Pritchard, O., & Bhreasail, Á. N. (2020). The case for value chain resilience. Management Research Review.

Maheswari, H., Yudoko, G., & Adhiutama, A. (2019). Government and Intermediary Business Engagement for Controlling Electronic Waste in Indonesia: A Sustainable Reverse Logistics Theory through Customer Value Chain Analysis. Sustainability.

Miethlich, B., & G. Oldenburg, A. (2019). The Employment of Persons with Disabilities as a Strategic Asset: A Resource-Based-View using the Value-Rarity-Imitability-Organization(VRIO) Framework . Journal of Eastern Europe Research in Business and Economics.

Mintz, O., J.Gilbride, T., & Lenk, P. (2021). The right metrics for marketing-mix decisions. International Journal of Research in Marketing , 32-49.

Munro, M. M. (2017). Analyzing external environment factors affecting social enterprise development. Social Enterprise Journal, 38-52.

Phadermrod, B., M.Crowder, R., & B.Wills, G. (2019). Importance-Performance Analysis based SWOT analysis. International Journal of Information Management, 194-203.

Pogorelova, E., Yakhneeva, I., & Agafonova, A. (2016). Marketing Mix for E-Commerce. International Journal of Enviornmental & Science Education .

Radpour, S., Mondal, M. A., & Kumar, A. (2017). Market penetration modeling of high energy efficiency appliances in the residential sector. Energy, 951-961.

Rizaldi, A. (2015). Control Environment Analysis at Government Internal Control System: Indonesia Case. Procedia - Social and Behavioral Sciences, 844-850.

S. Samusenko, A., S. Plaskova, N., & A. Prodanova, N. (2020). The Analysis of the External Environment to Determine the Practical Focus of Applied Research and Development in the Framework of Innovation. Complex Systems: Innovation and Sustainability in the Digital Age , 245–255.

Seema, S. (2016). Porter's Model: A Critical Examination . International Journal of Engineering and Management Research .

Thabit, T., & Raewf, M. (2018). The Evaluation of Marketing Mix Elements: A Case Study. International Journal of Social Sciences & Educational Studies.

Wang, L., Wang, Y., & Shi, L. (2022). Analysis of risky driving behaviors among bus drivers in China: The role of enterprise management, external environment and attitudes towards traffic safety. Accident Analysis & Prevention.

Zhao, Z. Y., Zuo, J., & Wu, P. H. (2016). Competitiveness assessment of the biomass power generation industry in China: A five forces model study. Renewable Energy, 144-153.