Accelerating adoption of new approach methodologies in regulatory decision making: an industry perspective
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Management practices and manufacturing firm responses to a randomized energy audit
Increasing the efficiency of industrial energy use is widely considered important for mitigating climate change. We randomize assignment of an energy audit intervention aimed at improving energy efficiency and reducing energy expenditures of small- and medium-sized metal processing firms in Shandong Province, China, and examine impacts on energy outcomes and interactions with firms’ management practices. We find that the intervention reduced firms’ unit cost of electricity by 8% on average. Firms with more developed structured management practices showed higher rates of recommendation adoption. However, the post-intervention electricity unit cost reduction is larger in firms with less developed practices, primarily driven by a single recommendation that corrected managers’ inaccurate reporting of transformer usage at baseline, lowering their electricity costs. By closing management-associated gaps in awareness of energy expenditures, energy audit programmes may reduce a firm’s unit cost of energy but have an ambiguous impact on energy use and climate change.
Affective integration in experience, judgment, and decision-making
The role of affect in value-based judgment and decision-making has attracted increasing interest in recent decades. Most previous approaches neglect the temporal dependence of mental states leading to mapping a relatively well-defined, but largely static, feeling state to a behavioral tendency. In contrast, we posit that expected and experienced consequences of actions are integrated over time into a unified overall affective experience reflecting current resources under current demands. This affective integration is shaped by context and continually modulates judgments and decisions. Changes in affective states modulate evaluation of new information (affect-as-information), signal changes in the environment (affect-as-a-spotlight) and influence behavioral tendencies in relation to goals (affect-as-motivation). We advocate for an approach that integrates affective dynamics into decision-making paradigms. This dynamical account identifies the key variables explaining how changes in affect influence information processing may provide us with new insights into the role of affect in value-based judgment and decision-making.
Determinants of consumer intention to use autonomous delivery vehicles: based on the planned behavior theory and normative activation model
Autonomous delivery vehicles (ADVs) that provide contactless services have attracted much academic and practical attention in China in recent years. Despite this, there is a lack of in-depth research on what motivates customers to embrace ADVs. The study integrates the theory of planned behavior (TPB) and normative activation model (NAM) and explores how environmental factors, situational factors, and individual factors affect original TPB constructs and ultimately consumers’ intention to use ADVs. Structural equation modeling was performed on survey data of 561 Chinese consumers through an online sampling platform. The results show that among the factors affecting consumer intention, word-of-mouth recommendations have the greatest impact, followed by perceived enjoyment, COVID-19 risk, ascription of responsibility, subjective norm, attitude, and perceived behavioral control. The results not only make important theoretical contributions to the technology acceptance fields but also provide helpful references to logistics enterprises, ADVs technology providers, and policymakers.
Exploring corporate social responsibility practices in the telecommunications, broadcasting and courier sectors: a comparative industry analysis
This study aims to dissect and understand the Corporate Social Responsibility (CSR) endeavours of organisations within Malaysia’s telecommunications, broadcasting, postal and courier services sectors, particularly those holding licenses from the Malaysian Communications and Multimedia Commission (MCMC). These sectors were chosen for this study due to their crucial role in Malaysia’s economy and society, their notable environmental influence, the regulatory and public attention they receive as well as the distinct challenges and opportunities they face in implementing CSR. Employing a qualitative methodology, the study utilises a semi-structured interview protocol to gather rich, detailed insights from top management across eight listed and non-listed companies. This approach ensures a comprehensive exploration of CSR types, practices and their implementation within the target sectors. Purposive sampling was adopted to select informants with specific expertise, ensuring that the data collected was relevant and insightful. The findings of this study underscore that while telecommunications firms actively participate in Corporate Social Responsibility (CSR) initiatives, their efforts predominantly benefit the broader society, with less emphasis placed on shareholders. Additionally, it was observed that environmental issues receive relatively minimal attention from these organisations. This diversity highlights the necessity for a more equitable CSR approach that caters equally to the needs of all stakeholders, including the environment. Such a strategy is crucial for cultivating a sustainable and ethically sound business environment. The implications of this research are manifold. For companies, it emphasises the critical nature of adopting an all-encompassing CSR strategy that fosters competitive advantage while promoting sustainable development. The study advocates for a paradigm shift towards CSR practices that are not only philanthropic but also prioritise environmental stewardship and value creation.
No evidence for decision fatigue using large-scale field data from healthcare
Decision fatigue is the idea that making decisions is mentally demanding and eventually leads to deteriorated decision quality. Many studies report results that appear consistent with decision fatigue. However, most of this evidence comes from observed sequential patterns using retrospective designs, without preregistration or external validation and with low precision in how decision fatigue is operationalized. Here we conducted an empirical test of decision fatigue using large-scale, high-resolution data on healthcare professionals’ medical judgments at a national telephone triage and medical advice service. This is a suitable setting for testing decision fatigue because the work is both hard and repetitive, yet qualified, and the variation in scheduling produced a setting where level of fatigue could be regarded as near random for some segments of the data. We hypothesized increased use of heuristics, more specifically convergence toward personal defaults in case judgments, and higher assigned urgency ratings with fatigue. We tested these hypotheses using one-sided Bayes Factors computed from underlying Bayesian generalized mixed models with random intercepts. The results consistently showed relative support for the statistical null hypothesis of no difference in decision-making depending on fatigue (BF0+ > 22 for all main tests). We thus found no evidence for decision fatigue. Whereas these results don’t preclude the existence of a weaker or more nuanced version of decision fatigue or more context-specific effects, they cast serious doubt on the empirical relevance of decision fatigue as a domain general effect for sequential decisions in healthcare and elsewhere.
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