The Impact of Corporate Sustainability and Technology Investment on Firm Innovation

Corporate sustainability is becoming an important component of corporate strategy, resulting in new areas of goal setting, planning, and process-level change. Despite the growing importance of corporate sustainability in organizations, there is a lack of research examining how the coexistence of corporate sustainability practices and a firm’s technology investment impacts critical processes such as innovation. In this study, we use resource orchestration theory and the information disclosure perspective to examine how the combination of a firm’s corporate sustainability efforts and technology investment can influence and impact a firm’s innovation process. Using a longitudinal data of S&P firms, from 2017 to 2020, we show that corporate sustainability performance, as reflected through ESG (environmental, social, and governance) measures, and technology investment positively impact a firm’s innovation process outcomes. Surprisingly however, the combination of these two individually contributing factors leads to a lower innovation performance. Implications for practitioners and academics are discussed. Keywords Corporate sustainability, ESG, innovation, information disclosure, resource orchestration, technolog

How Board of Directors’ Social Capital Enhances the Effectiveness of IT and R&D Resources Toward More Effective Innovation

A board of directors (BOD) plays a critical governance and strategic oversight role in an organization; acting as a fiduciary for shareholders, advising strategic decision making, and providing supportive resources and information to key decision makers. Especially critical is the role and contribution of corporate governance in guiding firm innovation. Such guidance has implications for investment in new products and services. In this paper, we examine the synergistic relationship between a firm’s BOD and technology and R&D inputs to innovation. We focus on the influence of the social capital of a BOD on different types of innovation. Our longitudinal findings show IT, R&D, and BOD social capital individually contribute to innovation performance, reflected in exploitative and exploratory innovation productivity. Moreover, BOD social capital enhances innovation enabled by IT activities. However, the combination of R&D activities and dimensions of BOD social capital leads to both negative and positive innovation performance

Resilience through Technology Intensity and International Related Management Experience: An Explorative Examination of European Firms during the COVID-19 Crisis

Recovering from disruption and responding to a crisis is becoming a major concern for firms, especially during the COVID-19 pandemic. Prior research suggests that in the presence of uncertainty and disruption, resilience is influential in retaining performance. Less is known, however, about how organizational and technological factors come together to build a resilient firm. Using organizational information processing theory (OIPT), our study helps to fill this gap by examining the interplay between technology intensity and international related management experience to build a resilient mechanism. The empirical findings show this resilience mechanism can strengthen business performance during times of crisis. Moreover, further analysis provides new insights based on the scope of a firm’s market, supply dependency, and its business sector. Specifically, the interaction of technology intensity with international related management experience makes a greater impact on the performance for firms that are operating and selling their products or services internationally, have more dependency on an international supply, and service firms. Our findings support the complementary role of international related management experience to build a resilient firm and provide managerial insights for crisis response strategies

The Impact of Data Analytics on Hospital Performance

The healthcare industry has yet to harness the full potential of data analytics in administrative and clinical care operations. Indeed, evidence of data analytics impacts on hospital operations is sparse. This study helps close this research gap by examining the effect of data analytics on hospital clinical operations. A conceptual model is proposed, anchored to dynamic capabilities theory. Using ten years of secondary data for more than 2,500 US hospitals, econometrics analyses provide evidence of a positive impact of clinical data analytical systems (CDAS) on patient experience. However, no similar evidence is found with overall hospital operational performance. Thus, while data analytics can have a targeted impact, organizational-wide effects appear to be more complex. Implications for practitioners and academics are discussed

The Role of Head-Mounted Display (HMD)-Based Meta-Apps in Advancing Healthcare

The Metaverse is an envisioned shared virtual environment enabled by technologies, such as virtual reality (VR), artificial intelligence (AI), cloud computing, and blockchain. Head-mounted displays (HMDs) are a VR technology that provide users a more immersive and engaging experience. Consequently, there is a growing interest in exploring the applications of HMDs in healthcare. HMDs can revolutionize healthcare by providing interactive environments for medical training, remote consultations, and others. In addition, HMDs can facilitate the unobtrusive collection of health data, enabling objective measurement of emotions, activity, and other digital biomarkers that are indicators of human performance or well-being. This data can be used along with digital phenotyping to design real-time, personalized health interventions that can surpass conventional interventions. In this study, we synthesize literature review articles that examine the use of HMDs in healthcare to provide a holistic view of the current HMD-based research in healthcare and outline future research directions

Investigation of respirable coal mine dust (RCMD) and respirable crystalline silica (RCS) in the U.S. underground and surface coal mines

Abstract Dust is an inherent byproduct of mining activities that raises notable health and safety concerns. Cumulative inhalation of respirable coal mine dust (RCMD) and respirable crystalline silica (RCS) can lead to obstructive lung diseases. Despite considerable efforts to reduce dust exposure by decreasing the permissible exposure limits (PEL) and improving the monitoring techniques, the rate of mine workers with respiratory diseases is still high. The root causes of the high prevalence of respiratory diseases remain unknown. This study aimed to investigate contributing factors in RCMD and RCS dust concentrations in both surface and underground mines. To this end, a data management approach is performed on MSHA’s database between 1989 and 2018 using SQL data management. In this process, all data were grouped by mine ID, and then, categories of interests were defined to conduct statistical analysis using the generalized estimating equation (GEE) model. The total number of 12,537 and 9050 observations for respirable dust concentration are included, respectively, in the U.S. underground and surface mines. Several variables were defined in four categories of interest including mine type, geographic location, mine size, and coal seam height. Hypotheses were developed for each category based on the research model and were tested using multiple linear regression analysis. The results of the analysis indicate higher RCMD concentration in underground compared to RCS concentration which is found to be relatively higher in surface coal mines. In addition, RCMD concentration is seen to be higher in the Interior region while RCS is higher in the Appalachia region. Moreover, mines of small sizes show lower RCMD and higher RCS concentrations. Finally, thin-seam coal has greater RCMD and RCS concentrations compared to thicker seams in both underground and surface mines. In the end, it is demonstrated that RCMD and RCS concentrations in both surface and underground mines have decreased. Therefore, further research is needed to investigate the efficacy of the current mass-concentration-based monitoring system

Accident analysis of mining industry in the United States - a retrospective study for 36 years

A retrospective study on accident analysis of the United States mines for 36 years was achieved using statistical analysis on the MSHA's accident databases between 1983 and 2018. A regression model of generalized estimation equation (GEE) was used for unbalanced panel data that provided 95,812 observations for 19,924 mine-ID-year in aggregate, coal, metal, and non-metal mines. The contributions of various parameters, including mine type, injured body part, days lost, age, and experience on the rate of accidents and injuries were investigated across the commodity types. The results showed coal miners in the East region are at a higher risk of accident. The results of regression analysis show that mine-tenured workers have a vital role in accident frequencies. Analysis of the injured body part on the injury rate indicates that the upper body injuries are the most significant among all mine types. Also, the fatality rate is significant in aggregate, and coal mines in comparison with metal and non-metal mines