"坐以待毙"还是"孤注一掷"OACHSSCD

This study probes into the phenomenon of digital cost stickiness and its implications for business strategies during digital transformation,contributing tremendously to the mushrooming academic exploration on digital cost dynamics.A game-theoretical model is constructed to delve into the strategic interactions between firms of varying sizes,which not only captures their dynamic decision-making processes,but also highlights the trade-offs between investment scale,profitability,and cost management.The model adequately reveals how digital investments by large firms generate both demonstration and competitive pressure effects,thereby encouraging smaller enterprises to adopt digital transformation and revealing the mechanisms underlying digital cost stickiness. The theoretical framework is substantiated by robust empirical analysis,by employing panel data from 1,950 firms spanning from 2015 to 2020,a pivotal period of digital convergence in China.An array of econometric models,comprising stickiness models,quantile regression,fixed effects quantile regression,generalized quantile regression,IV-quantile regression,and moderated mediation models,are universally employed to investigate the driving forces and effects of digital cost stickiness.As demonstrated by the findings,digital cost stickiness is pervasive across firms,irrespective of size or transformation motivations.Apart from that,the association between digital investment scale and stickiness is non-linear,with cost stickiness peaking at around 90％of a firm's digital budget allocation. To cope well with endogeneity,the study adopts an instrumental variable approach.The interaction between the distance from a firm's city to the nearest coastal port and the logarithm of national broadband access port count is employed as an instrument and estimated via the Method of Moments(MoM).As our findings illustrate,cost stickiness is generally weaker in low-cost firms,which benefit from more marked flexibility during early-stage investments,whereas high-cost firms face conspicuous stickiness on account of adjustment difficulties and long-term constraints.On this basis,corrected quantile regression methods further address sample selection bias,illustrating that revised stickiness estimates tightly coincide with baseline findings.These adjustments validate the theoretical predictions and demonstrate firms' cautious investment behavior,particularly when considering their scale and risk tolerance. Small-and medium-sized enterprises(SMEs)face significant demonstration and competitive pressure effects,thereby exacerbating cost stickiness and operational risks.Medium-cost firms,in particular,encounter financing constraints and slow cost recovery,necessitating further digital investments despite rising stickiness.As digital transformation scales augment,75％～90％of firms exhibit elevated sensitivity to macroeconomic fluctuations,mirroring a dual impact of escalating digital dependency and ongoing cost stickiness. Heterogeneity analysis suggests striking discrepancies across industries and ownership structures.State-owned enterprises(SOEs)incur higher digital transformation costs and exhibit more striking cost stickiness in contrast to non-SOEs,particularly in the product industry.Despite lower-than-expected returns in manufacturing and processing industries,SOEs serve as exemplars for digital innovation and technology diffusion,thus enabling smaller firms to adopt cutting-edge solutions.Private firms featured by weaker risk tolerance,are more sensitive to revenue fluctuations and macroeconomic shifts,triggering more intensive caution in digital transformation investment decisions. Stickiness effects vary across product life cycle management(PLM)scenarios.Specifically,high-cost firms exhibit the most noticeable stickiness in data analysis and process control scenarios,where efficient resource allocation and marginal adjustment costs are crucial.Business intelligence services and technical support scenarios display less marked stickiness effects,largely confined to auxiliary functions.Institutional implementation scenarios display balanced stickiness effects,reflecting their broader and more profound impact on resource allocation. More in-depth analyses explore lagged effects and production capacity differences.SMEs with lower digital maturity exhibit delayed responses to transformation efforts,entailing extended time frames to materialize cost and efficiency enhancements.High-capacity firms present resilience to cost stickiness on account of their ability to optimize digital investments,while low-capacity firms struggle with upfront costs and slower returns.These dynamics underscore the complex interplay of firm-level characteristics,transformation strategies,and broader economic conditions. To sum up,this study offers an all-round analysis integrating theoretical modeling,advanced econometric techniques,and actionable policy insights.It underlines the pivotal role of large firms in facilitating sector-wide digital transformation while providing fruitful guidance for firms and policymakers navigating the complexities of digitalization.