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Flights are often delayed owing to emergencies. This paper proposes a cooperative slot secondary assignment (CSSA) model based on a collaborative decision-making (CDM) mechanism, and the operation mode of flight waves designs an improved intelligent algorithm to solve the optimal flight plan and minimize the total delay of passenger time.

Taking passenger delays, transfer delays and flight cancellation delays into account comprehensively, the total delay time is minimized as the objective function. The model is verified by a linear solver and compared with the first come first service (FCFS) method to prove the effectiveness of the method. An improved adaptive partheno-genetic algorithm (IAPGA) using hierarchical serial number coding was designed, combining elite and roulette strategies to find pareto solutions.

Comparing and analyzing the experimental results of various scale examples, the optimization model in this paper is greatly optimized compared to the FCFS method in terms of total delay time, and the IAPGA algorithm is better than the algorithm before in terms of solution performance and solution set quality.

Based on the actual situation, this paper considers the operation mode of flight waves. In addition, the flight plan solved by the model can be guaranteed in terms of feasibility and effectiveness, which can provide airlines with reasonable decision-making opinions when reassigning slot resources.

This paper aims to explore the factors that influence innovation and productivity in small and medium-sized enterprises (SMEs) manufacturing enterprises in Colombia, in comparison with larger firms.

The study was based on firm-level panel data extracted from a census of Colombian manufacturing firms between 2007 and 2014. The authors used an adapted version of the Crepon-Duguet-Mairesse (CDM) sequential approach that interrelates R&D intensity, innovation outputs and productivity.

This study's findings indicate that investing in R&D has a positive impact on innovation in both SMEs and larger firms. However, the effect on productivity is significantly higher for SMEs. Evidence also suggests that the innovation performance of SMEs and larger firms is influenced by co-evolution among the firm's resources and capabilities, knowledge flows with external organizations, access to funding and knowledge appropriability conditions. However, highly qualified personnel, internal and commercial sources of funding, and market knowledge sourcing are crucial for innovation in SMEs. These conclusions are especially relevant for the design of industrial and innovation policies in developing economies, where innovation is a prerequisite for catching up and economic advancement.

The paper provides new empirical evidence on the determinants of innovation in SMEs, the mechanisms by which innovation capabilities and outputs affect its productive performance, and how the relationship between these dimensions varies with firm size in the context of a developing country.

Open innovation (OI), by now one of the major concepts for the analysis of innovation, is seen as a methodology for collaboratively designing and implementing solutions by engaging stakeholders in an iterative and inclusive service design process. This paper aims to empirically investigate OI capacities, defined as a cooperative, knowledge-sharing innovation ecosystem, and to explore how it can lead to improved performance of firms in Central and Eastern European (CEE) and Southeastern European (SEE) countries.

The study builds on the World Bank/European Bank for Reconstruction and Development (EBRD’s) Business Environment Enterprise Performance Survey (BEEPS) dataset for 2009, 2013 and 2019. Primarily, the research model was estimated using log-transformed ordinary least squares (OLS). Taking into consideration that this method might produce substantial bias, yielding misleading inferences, this study is fitting Poisson pseudo maximum likelihood estimators with robust standard errors and instrumental variable/generalized method of moments estimation (IV/GMM) approach for comparative results. Secondarily, the research model was tested using structural equation modelling (SEM) to investigate the relationship between five OI capacities and firm performance.

The findings indicate that there is a significant positive relationship between most OI capacities and firm performance, except for innovation, which did not show a statistically significant relationship with firm performance. Specifically, research and development (R&D), knowledge and coopetition are statistically significant and positively associated with firm performance, whereas transformation is statistically significant but negatively associated with firm performance. The IV/GMM estimations’ findings support the view that the firm performance is significantly affected by OI capacities, together with some control variables such as size, age, foreign ownership and year dummy to have a significant impact on firm performance.

This paper fills an identified gap in the literature by investigating the impact of OI on firm performance executed in the specific CEE and SEE country context.

This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite element simulation (FEM) and continuous damage mechanics (CDM) model, a fatigue life database is built. The stacked machine learning (ML) model's iterative optimization during training enables precise fatigue predictions (2.41% root mean square error [RMSE], R² = 0.975) for diverse structural components. Outliers are found in regression analysis, indicating potential overestimation for thickness transition specimens with extended lifetimes and underestimation for open-hole specimens. Correlations between fatigue life, stress factors, nominal stress and temperature are unveiled, enriching comprehension of LCF, thus enhancing solder behavior predictions.

This paper introduces stacked ML as a novel approach for estimating LCF life of SAC305 solder in various structural parts. It builds a fatigue life database using FEM and CDM model. The stacked ML model iteratively optimizes its structure, yielding accurate fatigue predictions (2.41% RMSE, R² = 0.975). Outliers are observed: overestimation for thickness transition specimens and underestimation for open-hole ones. Correlations between fatigue life, stress factors, nominal stress and temperature enhance predictions, deepening understanding of solder behavior.

The findings of this paper highlight the successful application of the SMLA in accurately estimating the LCF life of SAC305 solder across diverse structural components. The stacked ML model, trained iteratively, demonstrates its effectiveness by producing precise fatigue lifetime predictions with a RMSE of 2.41% and an “R²” value of 0.975. The study also identifies distinct outlier behaviors associated with different structural parts: overestimations for thickness transition specimens with extended fatigue lifetimes and underestimations for open-hole specimens. The research further establishes correlations between fatigue life, stress concentration factors, nominal stress and temperature, enriching the understanding of solder behavior prediction.

The authors confirm the originality of this paper.

This research aims to model the existing system of destination competitiveness, identifies leverage points and develop revised model to achieve sustainable competitiveness.

System dynamics is used as method of modeling destination competitiveness. Structure of model utilizes 9-factor model as reference. Leverage points are identified using system archetypes. Revised model is built with resource-based view (RBV). Case study was conducted in Samosir, Toba Lake. Data used are secondary data and results of in-depth interviews.

There are 3 sub-systemic characteristics (archetypes) that hinder competitiveness. They are limit to growth quality gap, fix that fails infrastructure and promotion, tragedy of common lake pollution. Destination was unable to meet tourist expectations. Tourists spending decreased, demand size was small. Industries are unable to increase capabilities. Professionals, entrepreneurs, local workers, supporting industries are less interested in entering industry. Government policies do not match with destination's needs. Lake as main attraction is getting polluted. To achieve sustainable competitiveness, destination must utilize their valuable, rare and inimitable (VRI) resources and capabilities to design unique experiences for tourists, hence sustainable.

Government policy should be shifted to prioritizing development of valuable, rare, inimitable and well-organized resources and capabilities of destination, to produce unique tourist experience and achieve sustainable competitiveness.

Methods and findings, combining system dynamics, system archetype, 9-factor model and RBV to achieve sustainable competitiveness is novel and can enrich tourism sustainable competitiveness theory/concept.

Science and technology parks (STP) are established to facilitate innovation and the rapid development of cutting-edge technologies. The innovation performance of tenants is the primary feature of all successful STPs globally. The purpose of this study is to investigate firms’ innovation and economic performance at the National Science and Technology Park (NSTP), Islamabad, Pakistan.

The CDM (the acronym of the three authors’ names, Crépon, Duguet and Mairesse) model following a two-stage approach was used to analyze the survey data of 105 tenants. The innovation performance of tenants was estimated through probit regression at Stage 1, and the economic performance of tenants given their innovation performance was examined at Stage II using Tobit regression and the Heckman model.

The findings suggest that compatibility of innovation with the existing competitive advantage of a firm increases the innovation performance of firms, whereas collaboration of firms with NUST for research and development has only a marginal effect on innovation performance. However, the tenant’s business and social networking were weak, possibly due to the short time spent on NSTP.

These STPs are expected to be hubs of technology development and transfer by fostering open innovation through internal and external collaborations. To the best of the authors’ knowledge, this is the first study to estimate the innovation performance of tenants at NSTP, the first fully integrated STP in Pakistan. Despite shortcomings, the innovation and economic performance of NSTP tenants warrant further public policy support to inculcate open innovation culture.

Recent work in the economics of innovation in developing countries increasingly considers the formality of business as a determining factor of economic development. However, current knowledge on how formality determines both innovation and business performance remains mixed. This article examines this relationship by analyzing, on the one hand, the role of formality on innovation and, on the other hand, the moderating effect of formality on the relationship between innovation and the performance of business in francophone Sub-Saharan Africa.

Based on a sample of 1,369 Cameroonian and Senegalese small and medium-sized enterprises (SMEs) from the International Development Research Center (IDRC), the Crepon Duguet et Maraise (CDM) technique was used to reduce the endogeneity bias inherent in this type of analysis.

The results show that formal companies have a better capacity for innovation. In addition, formality positively moderates the relationship between innovation and the performance of businesses in the case of product and commercial innovations. On the other hand, it negatively moderates the relationship between innovation and the performance for process and organizational innovations.

These results show that the advantages of formalization widely relayed by national public institutions and international organizations can present a risk for business if the expected gains are not accompanied by innovations.

This paper contributes to research by taking into account the heterogeneity of firms because it is one of the first to study formality as a moderator in the relationship between innovation and firm performance in Sub-Saharan African economies.

The purpose of this study is to examine the effect of knowledge and attitude on firms’ commitment to Halal standard practices in a developing nation’s food sector. Additionally, the moderating effect of gender on this association is explored.

The partial least squares-structural equation modelling (PLS-SEM) technique is used to analyse the results of a self-administered questionnaire completed by 200 internal Halal executive officers of multinational corporations and small and medium enterprises in a developing nation’s food sector.

The empirical findings reflect the significant role of attitude in influencing firms’ commitment to Halal standard compliance in the food sector and thereby contribute towards improving organisational performance. In more detail, male respondents were more likely than female respondents to have a favourable attitude toward Halal standards in the food industry. Additionally, a positive attitude can influence how employees are judged on their adherence to Halal standard processes. This encouraging outcome is the result of joint efforts by all government agencies, statutory bodies and private organisations involved in Halal practices.

Halal food producers should engender greater commitment to Halal standard practices within the buyer–supplier relationship due to the crucial nature of Halal concerns in food production. They should place a premium on strategic planning to safeguard the integrity of Halal food for consumption.

This study considerably advances the existing body of knowledge by applying the consumer decision model to explain the relationships between knowledge, attitude and firms’ commitment to Halal standard practices in the food industry of a developing nation, with gender serving as a moderating variable. The empirical findings addressed the research gap by offering noteworthy insight into a subject that has received minimal attention in prior studies.

This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that introduce innovations (the self-selection hypothesis) and if the introduction of innovations boosts TFP growth (the returns-to-innovation hypothesis). Second, the authors study the firm’s joint dynamic decision to implement process and/or product innovations. The authors use Colombian manufacturing data from the Annual Manufacturing and the Technological Development and Innovation Surveys.

This study uses a four-stage procedure. First, the authors estimate TFP using a modified version of Olley and Pakes (1996) and Levinsohn and Petrin (2003), proposed by De Loecker (2010), that implements an endogenous Markov process where past firm innovations are endogenized. This TFP would be estimated by GMM, Wooldridge (2009). Second, the authors use multivariate discrete choice models to test the self-selection hypothesis. Third, the authors explore, using multi-value treatment evaluation techniques, the life span of the impact of innovations on productivity growth (returns to innovation hypothesis). Fourth, the authors analyse the joint likelihood of implementing process and product innovations using dynamic panel data bivariate probit models.

The investigation reveals that the self-selection effect is notably more pronounced in the adoption of process innovations only, as opposed to the adoption of product innovations only or the simultaneous adoption of both process and product innovations. Moreover, our results uncover distinct temporal patterns concerning innovation returns. Specifically, process innovations yield immediate benefits, whereas implementing both product innovations only and jointly process and product innovations exhibit significant, albeit delayed, advantages. Finally, the analysis confirms the existence of dynamic interconnections between the adoption of process and product innovations.

The contribution of this work to the literature is manifold. First, the authors thoroughly investigate the relationship between the implementation of process and product innovations and productivity for Colombian manufacturing explicitly recognising that firms’ decisions of adopting product and process innovations are very likely interrelated. Therefore, the authors start exploring the self-selection and the returns to innovation hypotheses accounting for the fact that firms might implement process innovations only, product innovations only and both process and product innovations. In the analysis of the returns of innovation, the fact that firms may choose among a menu of three innovation strategies implies the use of evaluation methods for multi-value treatments. Second, the authors study the dynamic inter-linkages between the decisions to implement process and/or product innovations, that remains under studied, at least for emerging economies. Third, the estimation of TFP is performed using an endogenous Markov process, where past firms’ innovations are endogenized.

While implementing green innovation-driven strategies when facing growing grim environmental problems and the realistic demands of achieving high-quality development is increasingly urgent, changing abruptly is inevitably detrimental to the smooth functioning of social and economic development. Restrained by resources, innovation-driven strategy is a huge strategy for an organization to shift from traditional technological innovation to green innovation. Supports and implementation in green technology investment would necessarily crowd out other business investment and lead to reduction of innovation outputs and mount of financial uncertainty. Under the guidance of harmonious balance, the equilibrium allocation between green research and non-green counterpart is badly needed to be addressed for decision-makers inside and outside the organizations. The differentiated inputs of them would lead to different effects on organizational performance in practice.

The authors first conducted a Hausman test on green research intensity (GRI) and innovation performance, economic performance, social performance, and environmental performance, respectively. Adopting the fixed effects model for estimation seems accurate, if there is no significant heteroscedasticity shown in the BP test. The authors then adopted the least square dummy variable method to handle individual heterogeneity (Xia et al., 2020). After controlling the industry effect and time effect simultaneously, the results were consistent with that of fixed effects model, thereby eliminating the impact of heteroscedasticity.

The authors construct a multi-dimensional performance system—innovation performance, economic performance, social performance, and environmental performance—to probe into the influence of GRI from the resource-based view and allocation theory. Different performance does not benefit equally from increasing the intensity of green research. Performance increase may squeeze out the quantity of total innovation but can compensate quality for knowledge spillovers of green technology. The organization's growth and long-term value may be beneficial from the increase, but not the short-term financial performance. While the relationship between GRI and social performance has the characteristic of reverse U-curve, there has to be some scale of green research to gain considerable and nonlinear environmental performance. Low level of green research may increase pollution until green research has cross over the inflection point. These relationships are intensely moderated by the environmental regulation.

Because of the focus of this study is on the organizational performance of green research, the analysis comes with some limitations that should be addressed in future research. Data were inter-professional, with large enterprises and small businesses innovating green technology at the same time. Though the hypotheses presented here were grounded in existing theoretical rationale, the generality of this study cannot be assumed. Multi-performance of green activities in small- and medium-sized businesses should be further explored. Additionally, concrete index of the corresponding evaluation system constructed here contribute more to practical activities of green innovation. Refinement of synergy performance index is the task for future work. Further, grounded in Chinese context, the authors' results could be compared with other scenario with institutional heterogeneity to provide detailed evidences for institutional theory. Future studies could also move forward to longitudinal case study to delicately investigate the performance differentiation of green research when in different development stage.

First, what and how the authors do is novel as the authors use listed Chinese manufacturing companies to probe into the complex relationship between GRI and multiple performance rather than discussing the performance of green innovation input from a single perspective merely. Second, the authors systematically define the performance as economic performance, environmental performance, social performance and innovation performance in depth, which consider adequately the tangible and intangible value as well as internal and external benefits of green research. And finally, in the context of environmental regulation, the study discusses the differentiation of the increase of green research intensity from the perspective of resource constraints, providing reference for optimizing the resource allocation in green and non-green research and solving the decoupling between earnest social appeal and sluggish or reluctant green behaviors.