Impact of work from home on work-life balance: Mediating effects of work-family conflict and work motivation

In the aftermath of the recent pandemic, organizations around the world had the opportunity to assess the benefits and drawbacks of allowing the bulk of their employees to work from home (WFH). As a result, many organizations realize that by using technology, it is possible to shift a significant percentage of their workforce to permanently function from any location without being physically present at a designated workplace. Although the economic benefits for organizations that allow WFH seem to be clear, how factors related to perceptions of employees such as their work motivation (WM) and their work-life balance (WLB) caused by blurred boundaries between work and family at home are not clearly understood. Therefore, the primary goal of this study is to determine how WFH impacts WLB through the possible mediating effects of work-family conflict (WFC) and WM. A cross-sectional survey instrument was developed using Likert type measurement scales that were adopted from top-tier journals. The data was collected through convenient sampling from 249 managerial and non-managerial employees in Omani business organizations. The relationships were tested through structural equation modeling. The results indicate that WFH increases WFC and WM, while the relationship between WFH and WLB is mediated by WFC, but not by WM. The findings of this study have implications for both theory and practice

“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

“So what if ChatGPT wrote it?”:Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

“Real impact”: Challenges and opportunities in bridging the gap between research and practice – Making a difference in industry, policy, and society

Achieving impact from academic research is a challenging, complex, multifaceted, and interconnected topic with a number of competing priorities and key performance indicators driving the extent and reach of meaningful and measurable benefits from research. Academic researchers are incentivised to publish their research in high-ranking journals and academic conferences but also to demonstrate the impact of their outputs through metrics such as citation counts, altmetrics, policy and practice impacts, and demonstrable institutional decision-making influence. However, academic research has been criticized for: its theoretical emphasis, high degree of complexity, jargon-heavy language, disconnect from industry and societal needs, overly complex and lengthy publishing timeframe, and misalignment between academic and industry objectives. Initiatives such as collaborative research projects and technology transfer offices have attempted to deliver meaningful impact, but significant barriers remain in the identification and evaluation of tangible impact from academic research. This editorial focusses on these aspects to deliver a multi-expert perspective on impact by developing an agenda to deliver more meaningful and demonstrable change to how “impact” can be conceptualized and measured to better align with the aims of academia, industry, and wider society. We present the 4D model - Design, Deliver, Disseminate, and Demonstrate - to provide a structured approach for academia to better align research endeavors with practice and deliver meaningful, tangible benefits to stakeholders

“Real impact”: challenges and opportunities in bridging the gap between research and practice – making a difference in industry, policy, and society

Achieving impact from academic research is a challenging, complex, multifaceted, and interconnected topic with a number of competing priorities and key performance indicators driving the extent and reach of meaningful and measurable benefits from research. Academic researchers are incentivised to publish their research in high-ranking journals and academic conferences but also to demonstrate the impact of their outputs through metrics such as citation counts, altmetrics, policy and practice impacts, and demonstrable institutional decision-making influence. However, academic research has been criticized for: its theoretical emphasis, high degree of complexity, jargon-heavy language, disconnect from industry and societal needs, overly complex and lengthy publishing timeframe, and misalignment between academic and industry objectives. Initiatives such as collaborative research projects and technology transfer offices have attempted to deliver meaningful impact, but significant barriers remain in the identification and evaluation of tangible impact from academic research. This editorial focusses on these aspects to deliver a multi-expert perspective on impact by developing an agenda to deliver more meaningful and demonstrable change to how “impact” can be conceptualized and measured to better align with the aims of academia, industry, and wider society. We present the 4D model - Design, Deliver, Disseminate, and Demonstrate - to provide a structured approach for academia to better align research endeavors with practice and deliver meaningful, tangible benefits to stakeholders.</p