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The innovation creation literature primarily focuses on urban firms/regions or relies heavily on these data; less studied are rural firms and areas in this regard. The purpose of this paper is to employ a new firm-level data set, national in scale, and analyze characteristics that potentially influence innovation creation across rural and urban firms.

The authors use the 2014 National Survey of Business Competitiveness (NSBC) covering multiple firm-level variables related to innovation creation combined with secondary data reflecting the regional business and innovative environments where these firms operate. The number of patent applications filed by these firms measures their innovation creation, and the paper employs a negative binomial regression estimation for analysis.

After controlling for industry, county and state factors, rural and urban firms differ in their innovation creation characteristics and behaviors, suggesting that urban firms capitalize on their resources better than rural firms. Other major findings of the paper provide evidence that: first, for rural firms, the influence of university R&D is relevant to innovation creation, but their perception of university-provided information is not significant; and second, rural firms that are willing to try, but fail, in terms of innovation creation have a slight advantage over other rural firms less willing to take on the risk.

This paper is one of the first to analyze the 2014 NSBC, a firm-level national survey covering a wide range of innovation-related variables. The authors combine it with other regional secondary data, and use appropriate analytical modeling to provide empirical evidence of influencing factors on innovation creation across rural and urban firms.

This study aims to examine and understand the impact of reverse logistics adoption on firms' digitalization and collaboration activities. Specifically, leveraging the knowledge-based view, this study examines how adopting sustainable logistic practices (reverse logistics) prepares firms to embrace digitalization and encourages them to collaborate with other organizations.

The study used longitudinal survey data from two waves (2017 and 2019) from the Mannheim Centre for European Economic Research. The authors used the negative binomial regression analyses to test the impact of reverse logistics adoption on the digitalization and inter-organizational collaboration dependent count variables.

The study's findings highlight the usefulness of reverse logistics in enabling digitalization and inter-organizational collaboration. The results show that the firms investing in sustainable supply chains will be better positioned to nurture digitalization and inter-organizational collaboration.

For resource-bound managers, this study provides an important insight into prioritizing activities by highlighting how reverse logistics can facilitate digitalization and collaboration. The study demonstrates that the knowledge generated by reverse logistics adoption can be an essential pillar and enabler toward achieving firms' digitalization and collaboration goals.

The study is among the first to examine the effect of reverse logistics adoption on firm activities that are not strictly associated with the circular economy (digitalization and collaboration). Utilizing the knowledge-based view, this study reports on the additional benefits of reverse logistics implementation previously not discussed in the literature.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

Driven to improve the quality of higher education as an engine of growth and socio-economic development within Pakistan for 20 years, the Higher Education Commission (HEC) in Pakistan has focused on linking academics and professional services staff with their counterparts in various countries, including the UK, US, and Australia. In collaboration with the British Council, the PAK-UK initiative has been launched to offer deeper linkages between the academics and universities in the UK and Pakistan. This paper presents statistical analysis of data collected in a British Council project highlighting the gender inequalities of the current HEC strategy. The results suggest the potential for online opportunities to help close and amend this gender gap and improve higher education in Pakistan, and the PAK-UK initiative's role in contributing more broadly to the United Nations Sustainable Development Goals.

The purpose of this study is to establish a systematic framework to characterise the safety of air routes, in terms of separation minima infringements (SMIs) between en-route aircraft, based on the definition of models known as safety performance functions.

Techniques with high predictive capability were selected that enable both expert knowledge and data to be harnessed: Bayesian networks. It was necessary to establish a conceptual framework that integrates the knowledge currently available on the causality and precursors of SMIs with the hindsight derived from the analysis of the type of data available. To translate the conceptual framework into a set of causal subnets, the concepts of air traffic management (ATM) barrier model and event trees have been incorporated.

The model combines analytics and insights, as well as predictive capability, to answer the question of how airspace separation infringements are produced and what their frequency of occurrence will be. The main outputs of the network are the predicted probability of success for the ATM barriers and the predicted probability distribution of the vertical and horizontal separation of an aircraft in its closest point of approach.

The main contribution of this work is that, by virtue of the calculation capacity obtained, the network can be used to draw conclusions about the impact that a modification of the airspace and of the traffic, or operational conditions, would have on the effectiveness of the barriers and on the final distributions of distance between aircraft in the CPA, thereby estimating the probability of SMI.

This paper aims to estimate the determinants of the intensity of use of financial inclusion by households in Ghana.

Due to the reality of a household using one or more financial products or services, this study uses the generalised Poisson model applied to GLSS6 and GLSS7 data collected in 2012/2013 and 2016/2017 respectively, to estimate the determinants of the intensity of use of financial inclusion. To deepen the analysis, a multinomial probit model is also applied.

Results show that infrastructural variables such as roads, public transport and banks stimulate the intensity of financial inclusion. In addition, agricultural development characteristics such as markets and cooperatives are essential for the intensity of inclusion.

There is a need to incorporate how many services or depth of services that people use as part of the conceptualisation of financial inclusion, as this can provide more policy-relevant evidence to enhance priority setting in financial inclusion policies. Also, micro-level financial inclusion studies in agrarian economies should consider exploring agricultural development and infrastructure variables in the modelling framework. As lead to further studies, count models of financial inclusion should consider exploring cross-country analysis, the use of panel data, or other methodological approaches to provide more robust evidence.

Previous studies have not modelled financial inclusion based on a count model as a means of measuring intensity though conceptualisations highlight the fact that people use varied financial products or services. Following from this angle, to the best of the authors’ knowledge, this study provides the first attempt at analysing the underlying determinants of the number of financial products or services used by households.

To proactively draw efficient maintenance plans, road agencies should be able to forecast main road distress parameters, such as cracking, rutting, deflection and International Roughness Index (IRI). Nonetheless, the behavior of those parameters throughout pavement life cycles is associated with high uncertainty, resulting from various interrelated factors that fluctuate over time. This study aims to propose the use of dynamic Bayesian belief networks for the development of time-series prediction models to probabilistically forecast road distress parameters.

While Bayesian belief network (BBN) has the merit of capturing uncertainty associated with variables in a domain, dynamic BBNs, in particular, are deemed ideal for forecasting road distress over time due to its Markovian and invariant transition probability properties. Four dynamic BBN models are developed to represent rutting, deflection, cracking and IRI, using pavement data collected from 32 major road sections in the United Arab Emirates between 2013 and 2019. Those models are based on several factors affecting pavement deterioration, which are classified into three categories traffic factors, environmental factors and road-specific factors.

The four developed performance prediction models achieved an overall precision and reliability rate of over 80%.

The proposed approach provides flexibility to illustrate road conditions under various scenarios, which is beneficial for pavement maintainers in obtaining a realistic representation of expected future road conditions, where maintenance efforts could be prioritized and optimized.

A wetland is a place of tourist attraction, and tourism values play a key role in economic development. Among various services provided by a wetland, recreational services are increasingly valuable in the tourism sector. This paper aims to unfold the potential recreational values of the Dal Lake in Jammu and Kashmir, India.

The study uses individual travel cost methods (TCMs) and assesses its impact on regional development in terms of income and employment generation. A sample of 200 tourists is selected through an on-site survey on Dal Lake, and the demand for recreational visits and its value is estimated by employing the truncated Poisson regression model (TPRM) and un-truncated Poisson regression model (UTPRM). The consumers' surplus is estimated and tourists' benefit to visiting the wetland is explored.

On average, estimated consumers' surplus per visitor is Rs 6,250 (US$96.15) and Rs 25,000 (US$384.61) from respective models. The annual total recreational value of the lake is accounted for Rs 1713m (US$ 26m). This high consumer surplus (CS) and recreational values of the lake indicate large demand for its recreational facilities.

The study is based on primary data and thus, is original. The paper has implications for the policymakers to formulate sustainable management plans for the proper use of Dal Lake and tourism development.