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Exploring the factors affecting the implementation of corporate social responsibility from a strategic perspective

Business

Exploring the factors affecting the implementation of corporate social responsibility from a strategic perspective

C. Wu, F. Cheng, et al.

This study by Chao-Chan Wu, Fei-Chun Cheng, and Dong-Yu Sheh delves into the essential elements guiding the implementation of strategic corporate social responsibility. Using the strategic triangle perspective, the findings highlight 'company' as the most significant factor, with corporate image and innovation ability among the top influencers. Discover how these insights not only enrich theoretical frameworks but also enhance practical applications in CSR.

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~3 min • Beginner • English
Introduction
The study addresses how companies can implement corporate social responsibility (CSR) strategically rather than as a cost or purely altruistic activity. It frames CSR within the strategic triangle (company, customer/stakeholder, competitor), arguing that strategic CSR aligns social initiatives with core competencies to achieve both societal benefits and competitive advantage. The purpose is to identify and prioritize key factors influencing strategic CSR implementation to guide resource allocation and planning. The importance lies in overcoming firms’ lack of motivation to engage in CSR by demonstrating its strategic value and fit with business objectives.
Literature Review
The review first outlines CSR as firms’ responsibility toward societal and stakeholder interests, emphasizing integration with operations rather than standalone philanthropy. It then discusses strategic thinking and Ohmae’s strategic triangle (company, customer, competitor), proposing its integration with CSR to form strategic CSR. From this perspective, three main factors are specified: (A) Company resources and assets (human resources, financial capacity, corporate image); (B) Stakeholders affected by or influencing the firm (purchase intention, investment intention, reputation risk, government relations); (C) Competitors and relative advantage (entry barrier, price premium, innovation ability). Arguments and prior evidence support each sub-factor’s relevance: human and financial resources enable CSR execution; corporate image as an intangible asset strengthened by CSR; consumers’ purchase intentions influenced by CSR; investors’ preferences for stable, responsible firms; media dynamics and reputation risk management; government relations improved by proactive CSR; potential for price premiums among socially conscious consumers; CSR as a moat raising entry barriers; and CSR-linked innovation improving development and processes. These informed a hierarchical network structure of factors.
Methodology
The study applies the Analytic Network Process (ANP) to a hierarchical network of factors derived from literature and expert input. The structure includes one goal (identify factors affecting strategic CSR), three main factors (company, stakeholder, competitor), and ten sub-factors: Company: financial capacity (A1), human resources (A2), corporate image (A3); Stakeholder: purchase intention (B1), investment intention (B2), reputation risk (B3), government relations (B4); Competitor: entry barrier (C1), price premium (C2), innovation ability (C3). Expert judgments were collected via ANP pairwise comparison questionnaires to assess: (1) main factors, (2) sub-factors within each main factor, and (3) interdependencies among factors. Pairwise comparisons used Saaty’s 1–9 scale. Priority vectors and maximum eigenvalues were computed; consistency of each matrix was checked using CI and CR (threshold CR < 0.1). A supermatrix capturing interdependencies was constructed, normalized to a weighted supermatrix, and raised to limiting powers to obtain a limit supermatrix, yielding global weights. Data were aggregated using geometric means across experts and analyzed with Super Decisions V3.2. Note: The paper reports two counts for experts; the methods narrative mentions 12 CSR professionals with ~10 years’ experience and 100% response, while the results section details 15 experts (10 industry, 5 academia; average 12 years) whose responses were analyzed and reported (Table 5).
Key Findings
- Main factor weights (without dependencies): Company 0.4992; Stakeholder 0.3310; Competitor 0.1698. - Sub-factor priorities within each main factor (local weights): Company: Financial capacity 0.4650; Human resources 0.2271; Corporate image 0.3079. Stakeholder: Purchase intention 0.4125; Investment intention 0.2797; Reputation risk 0.2015; Government relations 0.1063. Competitor: Entry barrier 0.3237; Price premium 0.1980; Innovation ability 0.4783. - Global weights from the limit supermatrix (considering dependencies): Corporate image 0.1779 (rank 1); Innovation ability 0.1653 (2); Reputation risk 0.1282 (3); Financial capacity 0.1264 (4); Investment intention 0.1237 (5); Human resources 0.0985 (6); Purchase intention 0.0944 (7); Price premium 0.0337 (8); Government relations 0.0303 (9); Entry barrier 0.0216 (10). - The sub-factors under Company and Stakeholder together account for approximately 0.4028 and 0.3766 of the total weight, respectively, indicating these two clusters contribute nearly 80% of influence on strategic CSR implementation.
Discussion
The findings support the strategic CSR framework rooted in the strategic triangle. Company-related capabilities and assets dominate, with corporate image emerging as the most critical lever: CSR can strengthen public perception and serve as intangible capital, guiding strategic planning and competitive positioning. Financial capacity’s prominence underscores the need to budget and align CSR investments with organizational resources to ensure execution. Stakeholder-related factors (notably reputation risk and investment intention) show that proactive CSR can mitigate reputational exposure, enhance investor appeal, and influence consumer behavior, reinforcing CSR’s role in stakeholder relationship management. Competitor-related elements highlight CSR’s contribution to innovation—embedding CSR into product development and processes can yield efficiency and differentiation benefits; CSR can also enable price premiums among certain consumer segments and contribute to competitive moats, though these are less influential than image and innovation overall. Collectively, the prioritized factors clarify how CSR can be integrated with core strategy to achieve both social outcomes and business advantages, directly addressing the motivation barrier by reframing CSR as a source of value and competitiveness rather than a cost.
Conclusion
The study integrates Ohmae’s strategic triangle with CSR to conceptualize strategic CSR and empirically prioritize the factors affecting its implementation. Using ANP on a hierarchical network of 3 main factors and 10 sub-factors, it identifies Company as the most influential cluster and highlights corporate image, innovation ability, reputation risk, financial capacity, and investment intention as the top drivers. Managerially, the framework helps firms align CSR with core competencies, stakeholder management, and competitive positioning; it guides resource allocation toward high-impact areas and supports embedding CSR into strategic planning so CSR is viewed as value-generating. Methodologically, ANP demonstrates utility in handling interdependencies among qualitative criteria to yield actionable priorities. Future research can expand the factor set through qualitative elicitation (e.g., focus groups, nominal group technique, in-depth interviews) and apply fuzzy ANP or hybrid methods to address judgment ambiguity and enhance robustness.
Limitations
- Factor selection relied on literature review, potentially constraining the factor space; additional qualitative methods (focus groups, nominal group technique, in-depth interviews) could uncover further relevant criteria. - The study employed ANP as a single quantitative method; incorporating fuzzy numbers into ANP or combining with other multi-criteria techniques could better handle uncertainty in expert judgments. - The paper reports inconsistent expert sample descriptions (12 vs. 15 experts); while results present analyses for 15 experts, clarifying sampling and data integration would strengthen methodological transparency.
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