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This paper aims to describe how one medical library implemented a new scheduling system, initiated data analysis and modified its regularly scheduled workshop program because of evidence-based decision-making. Academic libraries that struggle with workshop attendance may use this process as a model.

Workshop registration data analysis focused on registrants' affiliation, role and location, and how registrants learned of workshops. Workshop attendance data analysis focused on which workshops, days, times of the day and months had the highest attendance. The analysis led to changes in marketing and targeted scheduling of future workshops by the time of day, day of the week and month of the year.

Data collected for four years, fall 2018 – summer 2022 (12 semesters), shows a steady increase in the number of people attending library workshops. The increase in attendance and ROI experienced after the changes implemented at Ruth Lilly Medical Library (RLML) is significant as libraries often struggle with attendance, marketing and return on investment when offering ongoing educational workshops.

Many libraries offer ongoing workshops with low attendance. This article provides an example of how one library changed software and registration and implemented evidence-based decision-making related to scheduling which may have contributed to an increase in workshop attendance. Other academic libraries might consider adopting similar software and evidence-based decision-making to improve their library workshop service.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

Most college athletics department have not sold corporate naming rights to their athletics facilities. Popp et al. (2016) suggests two primary reasons: (1) difficulty in determining proper valuation and (2) fear of stakeholder backlash. The purpose of the current study is to address both concerns by utilizing a hedonic pricing model predicting collegiate naming rights values and utilizing fixed-effects models to determine if consumer behavior (event attendance and donations) is impacted by a corporate name change.

Data from 110 naming rights agreements among NCAA Division I programs were examined, alongside market-related variables, institution-related variables and venue-related variables. Utilizing hierarchical model building to reduce independent variables and OLS regression modeling, significant relationships with annual value of naming rights agreements were uncovered. Fixed effects models were utilized to determine if naming rights impacted attendance and donations.

A final model explained more than 53% of the variance in average annual value of naming rights agreements, with three significant factors: (1) attendance, (2) all-time winning percentage and (3) venue construction cost. Fixed-effects models revealed no significant differences in attendance or donations after a naming rights deal was signed.

Corporate naming rights agreements for college athletics facilities are a recent phenomenon. While a similar study examining drivers of collegiate sport naming rights was previously conducted, the current study revealed a shifting marketplace. In addition, no prior study has examined the impact of a corporate naming rights agreement on future attendance and donations.

The transtheoretical model (TTM) has been applied to varying areas of physical health, e.g. diabetes. However, research into its applicability to psychotherapy is mixed. The TTM is applied through the University of Rhode Island Change Assessment (URICA). Investigating the utility of the URICA is needed to improve patient care and outcomes. This study aims to assess whether the URICA scores relate to patient outcomes; patient attendance; practitioner ratings of patient readiness, appropriateness, insight, motivation and potential for improvement; and to explore practitioner’s perspectives on the URICA.

Correlational methods were used to assess the relationship between the URICA and therapeutic outcome, attendance and practitioner-rated areas. Content analysis was used to analyse practitioner qualitative data.

The URICA did not correlate with either therapeutic outcome or attendance. A significant negative correlation was found between the URICA and practitioner-rated appropriateness of the referral. This means practitioners perceived individuals with lower URICA scores to be a more appropriate referral, despite the score indicating a reduced readiness to change. Qualitative categories included positive views, negative views, ambivalence and changes to measure and process. To conclude, the URICA does not explain a patient’s outcome or attendance. The URICA may not be appropriate to use in its current format in mental health services; therefore, assessing the TTM verbally may be more helpful.

This study provides research into suitability of using the URICA to assess the TTM and its applicability to attendance and outcome in psychological therapies.

This paper defines and assesses student learning patterns under the influence of problem-based learning (PBL) and their classification into a reasonable minimum number of classes. Study utilizes PBL implemented in an undergraduate Statistics and Operations Research course for techno-management students at a private university in India.

Study employs an in situ experiment using a conceptual model based on learning theory. The participant's end-of-semester GPA is Performance Indicator. Integrating PBL with classroom teaching is unique instructional approach to this study. An unsupervised and supervised data mining approach to analyse PBL impact establishes research conclusions.

The administration of PBL results in improved learning patterns (above-average) for students with medium attendance. PBL, Gender, Math background, Board and discipline are contributing factors to students' performance in the decision tree. PBL benefits a student of any gender with lower attendance.

This study is limited to course students from one institute and does not consider external factors.

Researchers can apply learning patterns obtained in this paper highlighting PBL impact to study effect of every innovative pedagogical study. Classification of students based on learning behaviours can help facilitators plan remedial actions.

1. Clustering is used to extract student learning patterns considering dynamics of student performances over time. Then decision tree is utilized to elicit a simple process of classifying students. 2. Data mining approach overcomes limitations of statistical techniques to provide knowledge impact in presence of demographic characteristics and student attendance.

Parenting programmes are increasingly a feature of services and policies aimed at improving outcomes for children and families and tackling inequality, yet they remain underused. This study aims to assess parent engagement and retention in the parent and infant (PIN) programme – a universal, multi-component intervention designed to support parents from birth to when their children reach two years of age. The programme can be tailored to parent/community needs but also includes standardised core elements including two Incredible Years parenting programmes. Programme provider perspectives on recruiting and supporting participation were also explored.

A mixed methods study was conducted involving parents (n = 106) and programme providers involved in the PIN programme. Logistic regression analyses were used to assess the impact of participant demographic characteristics on the likelihood of programme engagement and attendance. Semi-structured interviews explored facilitators’ experiences of parent recruitment and engagement, as well as barriers and facilitators of parental attendance.

First-time mothers were more likely to initially enrol in the PIN programme than younger or lone parents. However, older age and married/cohabiting status were the strongest predictors of attending at least one-third of programme sessions. Qualitative findings highlighted the importance of relationship building and connection in supporting participant recruitment and engagement. Practical and psychological barriers to programme participation are also described.

The findings shed light on factors that influence engagement and attendance in universal, early parent support programmes. Barriers to parent engagement are multi-layered and tailored strategies to promote uptake of parenting programmes are needed.

This paper aims to examine the effects of corporate governance mechanisms (board chairman independence, board independent director meeting attendance, audit committee size and audit committee meetings) on the environmental, social and governance (ESG) and its individual component disclosures of listed firms in Saudi Arabia.

The study used unbalanced panel data obtained from the Bloomberg data set over 11 years, from 2010 to 2020.

The findings indicate that board chairman independence (BCI) and audit committee size (AC size) have a significant negative and positive association with ESG disclosure, respectively. However, the results show that board independent director meeting attendance (BIMA) and audit committee meetings (AC meetings) do not significantly influence ESG disclosure. Regarding the individual dimensions (components), the results show that only BIMA has a significant negative association with environmental disclosure. Besides, only BCI and AC meetings have a significant positive association with social disclosure. Also, only BIMA and AC size have a significant positive and negative relationship with governance disclosure, respectively.

The study used a sample of 29 listed companies in Saudi Arabia. Each firm has at least four years of ESG disclosures. Besides, the paper considered only four corporate governance attributes, comprising two each for the board and audit committee.

The results provide insights to regulators, boards of directors, managers and investors to enhance ESG and its components’ reporting toward the sustainable operations and better performance of Saudi firms.

This study is among the few that provide empirical evidence on how some essential corporate governance attributes that have not been given adequate attention by prior studies (board chairman independence, board independent directors’ meeting attendance, audit committee size and audit committee meetings) influence not only ESG reporting as a whole but also its individual dimensions (components).

This study investigates the effects of elements of corporate governance along with firm specific variables on the financial leverage of listed Indian firms in the context of agency conflicts and new governance laws.

A series of panel ordinary least squares as well as fixed/random effects regression models of book and market value of financial leverage on variables of corporate governance (board size, board composition, board meeting, board attendance and board gender) along with a set of control variables (asset tangibility, firm size, growth, liquidity and profitability) were estimated by employing 113 listed Indian firms during 2010–2021. Dynamic panel generalized method of moments models were also estimated to check the robustness of empirical results. Further, the full sample of firms was divided into small and large board sized companies using the median approach to investigate differences between small and large board characteristics on financial leverage.

The evidence predominantly suggested that the governance variables have significant impact on leverage ratios of selected firms. Governance variables such as board size, composition, attendance and gender are significantly found to be reducing the financial leverage of firms indicating that in general these attributes in a way, through monitoring managers, put pressure on them to pursue lower financial leverage. Board meeting is found to be positive and significantly related with financial leverage suggesting that the frequency of meetings signals its monitoring ability that may influence lenders' risk assessment lowering borrowing cost. The results on small and large board sized companies indicate that firms with small boards relatively issue more debt compared to firms with large boards suggesting that small boards adopt high debt policy.

The main policy implication of the study is that elements of internal corporate governance is a significant governance tool that has the potential to reduce agency conflict between the managers and agents through monitoring and decision making that has tangible effects on critical corporate decisions such as capital structure choices.

This paper contributes to the existing literature by bringing new evidence relating to agency conflicts and capital structure decisions in an emerging market like India post adoption of new regulations related to corporate governance specified in Clause 49 of Securities and Exchange Board of India and Companies Act, 2013 as there is significant dearth of such empirical work.

This study investigated the micro–macro link in the hospitality and tourism (H&T) sector, specifically considering whether the gender diversity, independence and board attendance rates of H&T firms' boards, alongside the moderation effect of board policies, played a significant role in tourism sector performance.

The 2011–2018 data were retrieved from the World Bank and the Thomson Reuters Eikon databases, and fixed effects panel regression was conducted.

While female directors were a significant driver of tourism sector performance in terms of tourist arrivals and tourism receipts, independent directors were effective in improving tourist arrivals only. Furthermore, moderation analyses demonstrated the inefficacy of board policies in enhancing these directors' contributions to the sector's development. Moreover, the findings revealed the inefficiency of board meetings.

Concerning the efficacy of board policies, the results suggest that firms' boards should review and revise their policies. Surprisingly, while board-diversity policies made no difference to female directors' role in the sector's development (although females were influential), board-independence policies produced unexpected results. In the absence of a board-independence policy, independent directors are influential, but if a policy exists, they are not.

Although prior firm-level studies tested whether board characteristics enhanced firms' performance in the H&T sector, they did not investigate whether board characteristics promoted tourism sector performance. Moreover, the moderating effect of board policies on boards' structures and tourism sector performance has not yet been examined.

Football exists and evolves in a dynamic ecosystem, displaying a massive and multidimensional influence on most contemporary societies, and football has grown into a significant industry with a plethora of stakeholders. This research is the first to comprehensively identify the key industry stakeholders and their distinct value, from the individual club perspective, and to conceptualise and test their interrelationship toward the development of a corresponding framework of club benefits.

The study applied a multilevel approach to collect and verify qualitative data. It initially developed a preliminary conceptual framework, which was first validated by an expert panel and was subsequently extensively tested in the Cyprus-specific context, which offered fertile ground for such a study. The empirical stage rested on 41 semi-structured, face-to-face interviews with very high-ranking individuals from the top nine football clubs, as well as with key industry stakeholders.

Though the examined industry is partly in line with international norms, it is also highly affected by unique characteristics that alter the various stakeholders' role, producing (even negative) value of varied typologies that is directly linked with the industry's financial, sporting, cultural and social conditions.

The research ultimately presents scholars, practitioners and policymakers with a systemic and comprehensive understanding of the individual club stakeholder value offerings, delivers a tested framework as a tool for social and business management and prescribes future avenues for research, governance and practice.

Extant studies on the subject are either partial or focus on individual stakeholders and evidently lack requisite scientific comprehensiveness. The current research bridges this significant gap in knowledge by exhaustively identifying the key industry stakeholders, explicating their relative social, economic or other value in the individual club perspective and developing a value-based stakeholder framework.