Factors that Influence the Learning Curve: Evidence from Cost Behavior in Clinical Labs*

Clinical labs belong to a mature industry and fulfill a critical function in the health-care value chain. We examine factors that influence the opportunity, motivation, and ability to learn in clinical labs. We hypothesize that with respect to learning about cost: (i) organizational design, such as the extent of outsourcing can impede the opportunity to learn, (ii) quality focus (measured by mortality rates and length of stay (LOS)) can reduce the motivation to learn, and (iii) related task variety (measured by product-mix breadth) and information technology investments can enhance the ability to learn. Our empirical tests calibrate learning effects on disaggregate (technical and supervisory hours and cost) and aggregate (salary and total direct cost) cost and time pools. Using longitudinal data from clinical labs in California for the period 1997–2015, we find that clinical labs with greater cumulative output have lower average costs, consistent with learning effects in clinical labs. We also find results consistent with our hypotheses about the contextual factors that influence learning rates in clinical labs. Our findings contribute to a better understanding of learning rates with implications for budgeting, forecasting, and performance measurement. The results highlight that learning can be a crucial source of cost reduction in health-care settings.     

Antecedents of intention to use chatbots in service encounters: A meta-analytic review

The trend of using artificial intelligence based chatbots for service encounters has seen a significant spike in recent times. Many studies have attempted to explain the adoption of the technology for various service applications; this study synthesizes the literature through a meta-analysis, for which data from 70 independent studies, with a combined sample size of 20,026 was considered, to understand the influencers of the attitude and intention to use chatbots for service encounters. In addition, this study also sought to understand the moderating role of the culture, the technological characteristics captured through the variables transactional/non-transactional, and informative/entertaining of the hypothesized relationships. Meta structural equation modelling (meta-analytic SEM) was used to analyse the data. The results indicate playfulness, attitude, usefulness, facilitating condition and social influence of the chatbots are the key factors in influencing user adoption. Further, technological characteristics and culture were found to significantly moderate certain relationships in the model. Practical and theoretical implications have also been discussed.     

Financial controller turnover: An early warning sign of deteriorating financial reporting quality

This study examines the relation between financial controller turnover and public firms’ financial reporting quality. Exploiting a special institutional setting in China, where financial controllers along with CEOs and CFOs are required to attest to the accuracy and completeness of firms’ annual reports, we find that: (a) financial controller turnover is negatively associated with financial reporting quality, (b) the negative relation between financial controller turnover and financial reporting quality is more pronounced in non-state-owned enterprises, in firms with weaker corporate governance, and in areas with higher regulatory enforcement intensity, and (c) financial controller turnover is not related to real earnings management. Further analyses show that financial controller turnover is associated with the incidence of subsequent financial report restatements and enforcement actions by the China Securities Regulatory Commission (CSRC). Financial controller turnover also precedes top executive turnover and can be viewed as an early warning sign of deteriorating financial reporting quality. Such information content is incremental to that of top executive turnover. Our analyses also show that firms with financial controller turnover have higher initial stock returns but underperform their counterparts in the long run.