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This study seeks to illuminate the managerial tensions inherent in implementing scaled agile (on the organizational, top management, middle management and team levels) and to frame these challenges within the broader context of project management.

The study adopts a grounded theory approach and delves into a qualitative dataset sourced from 34 interviews with subject matter experts actively engaged in scaling agile initiatives within large organizations spanning various industries. Additionally, the data have been enriched through a comprehensive literature review of the existing body of knowledge on scaling agile.

As a result of our investigation, we propose a framework of managerial tensions in scaling agile in large corporate settings and a series of research propositions and questions that may contribute significantly to the body of knowledge surrounding the phenomenon of “deprojectification” and propose agenda for the future studies in the field of project management.

The study also carries significant managerial implications. Firstly, based on the insights from the practice of scaling agile in large corporate setting, management can build awareness of the challenges inherent of transitioning to agile practices. This may help to anticipate the possible problems and proactively develop strategies how to address them. Secondly, management can be instructed about contingencies inherent in scaling agile, along with the potential disfunctions and side effects (unintended outcomes) that may emerge during the transition process. Thirdly, project management practitioners can gain insights on how scaling agile may cause shifts in the approach to managing projects, project team management and competencies that need to be developed to cope with environments where various approaches to managing projects coexist.

These insights can aid in the agile transition process, beginning with directing managerial attention toward contextual factors and progressing through potential challenges at the organizational, top management, middle management and team levels. Furthermore, the study highlights possible dysfunctionalities and side effects of scaling agile, shedding light on the “dark side” of agile.

The study contributes to the expansion of the empirical database on the implementation of agile practices in large organizational settings. It plays a role in defining and delineating the phenomenon of scaling agile within the context of project management and outlines a research agenda for future project management studies. Additionally, our study adds to the ongoing discourse surrounding the “deprojectification” effect that can occur during the scaling of agile. Lastly, it establishes connections between project management and software development literature regarding the implementation of agile at scale.

In this paper, the authors empirically and theoretically analyze the scaling and control of talent development to highlight an important part of commercialization in football clubs, especially in the light of a growing transfer market.

Conducting a single case study of a Swedish football club, the authors adapt a view of the club as a “high-intensity” organization (Alvesson and Kärreman, 2004), one that inherently relies on strong identification of employees and the fostering of talent. This view allows us to detail the importance of both socio-ideological and technocratic forms of control involved in the talent development process.

The authors show how socio-ideological and technocratic forms of control were combined to establish the football club as a “talent factory” in the league, as well as the corresponding challenges when scaling talent development activities and how these challenges were handled. In doing so, the authors contribute to the broader accounting literature on talent- and human resource management, as the authors provide an example of how football clubs may commercialize without necessarily violating their fundamental sports values.

Talent management has mainly been studied in terms of increasing player wages and a focus on the cost of talent. As opposed to these perspectives, the authors highlight the revenue potential in developing players in the light of a growing transfer market and the relevance of talent development for the commercialization of football clubs.

This study aims to provide a contextualized look at the artisan sector in Zambia and asks: What factors contribute to scaling positive impact in artisan ventures in Zambia, and how can these factors be leveraged to promote positive economic, social and environmental outcomes for women and their communities.

This study uses an explanatory sequential mixed-methods approach to gain a multi-layered understanding of artisan craft social enterprises in Zambia.

Purpose is found to be the primary driver of social and environmental impact in artisan social enterprises in Zambia, with female leadership a critical factor. Access to finance, markets and resources are also essential to help these organizations achieve their social missions.

While this study provides valuable insights into the artisan sector, its scope was limited to the Zambian context, making the generalizability of the findings to other geographies uncertain.

This research makes a valuable contribution to the literature on social enterprises by highlighting the critical role of female leadership and purpose in driving positive impact in artisan businesses in Zambia. Additionally, the study underscores the importance of understanding the mechanisms through which artisan social enterprises create positive change. The study highlights the importance of artisan craft employment for women in Zambia and illustrates the impact of Zambian artisan ventures, both formal social enterprises and informal businesses, on creating positive social and environmental impacts in the country.

This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.

This study uses a best–worst discrete choice experiment (BWDCE) and compares the outcome with that of the purchase intention scale, an established probabilistic measure of purchase intention. The total sample consists of 409 fans of three soccer teams sponsored by three different competing brands: Nike, Adidas and Puma.

With sports sponsorship, fans were willing to pay more for the sponsor’s product, with the sponsoring brand obtaining the highest market share. Prominent brands generally performed better than less prominent brands. The best–worst scaling method was also 35% more accurate in predicting brand choice than a purchase intention scale.

Future research could use the same method to study other types of sponsors, such as title sponsors or other product categories.

Sponsorship managers can use this methodology to assess the return on investment in sponsorship engagement.

Prior sponsorship studies on brand equity tend to ignore market share or fans’ willingness to pay a price premium for a sponsor’s goods and services. However, these two measures are crucial in assessing the effectiveness of sponsorship. This study demonstrates how to conduct such an assessment using the BWDCE method. It provides a clearer picture of sponsorship in terms of its economic value, which is more managerially useful.

Many existing trajectory optimization algorithms use parameters like maximum velocity or acceleration to formulate constraints. Due to the ignoring of the quadrotor actual tracking capability, the generated trajectories may not be suitable for tracking control. The purpose of this paper is to design an online adjustment algorithm to improve the overall quadrotor trajectory tracking performance.

The authors propose a reference trajectory resampling layer (RTRL) to dynamically adjust the reference signals according to the current tracking status and future tracking risks. First, the authors design a risk-aware tracking monitor that uses the Frenét tracking errors and the curvature and torsion of the reference trajectory to evaluate tracking risks. Then, the authors propose an online adjusting algorithm by using the time scaling method.

The proposed RTRL is shown to be effective in improving the quadrotor trajectory tracking accuracy by both simulation and experiment results.

Infeasible reference trajectories may cause serious accidents for autonomous quadrotors. The results of this paper can improve the safety of autonomous quadrotor in application.

Digitalisation is perceived as a new process that may add value to firms. Current theoretical understanding assumes it should be part of a firm's strategy to respond to multiple pressures in the business environment. This paper explores the occurrence of digitalisation in a rare context, that of the English agricultural industry in the United Kingdom, a place disproportionality filled with family firms. The general understanding of digitalisation in family firm settings remains embryonic. The authors' explorations make theoretical contributions to research at the intersection of rural entrepreneurship, family business and innovation.

Utilising a purposive, qualitative approach, primary data was collected from multiple interviews with 28 UK family farms, and secondary data from another 164. Interview transcripts were coded using NVivo, along with secondary data from reports, observations and websites.

The authors present empirical evidence illustrating how digitalisation manifests incrementally and radically in different types of family farms. The authors present a model that shows the areas of farming that have, and continue to be, digitalised. This increases analytical precision when identifying digitalisation activities that differ depending on the strategy to either scale or diversify. The authors propose that incremental digitalising occurs to a great extent during a scaling strategy, and that radical digitalising occurs to a smaller extent during diversification strategies in family farms.

This research uses a sample of family-run farms from the UK agricultural sector to explore nuanced elements of digitalisation. It should therefore be explored in other types of family firms located in different sectors and geographies.

This research is important because family farms are under increasing pressure and have limited financial resources to deal with the digitalisation agenda. Therefore, empirical evidence helps other farms in similar situations. The authors found digitalisation investments, that tend to be capital intensive, only matter for scalers and less so for diversifiers. Family farms can use the model presented as a tool to evaluate their farm. The tool helps them define what to do, and ideate the potential activities that might be digitalised, to feed into their wider strategy.

Family firms, in particular farms, are critical to many economies. The general consenses currently assumes all family firms should digitalise, yet the authors' evidence suggests that this is not the case. It is important to create policies that are sensitive to the needs of different types of businesses, in this case between family firm scalers and diversifiers, instead of simply incentivising digitalisation using a blanket approach usually by offering financial aid. Understanding how digitisation can support (or not) family firm resilience and growth in an effective and efficient manner can have significant benefit to individual firms, and across industries.

The proposed model extends theoretical understanding linking strategy, digitalisation activity and innovation in family farms. It shows that digitalisation is a key building block of scaling strategies, maximising digitalisation to increase efficiency. Yet, diversifying family farms minimise digitalisation, whereby they only digitalise a small amount of the farming activity. This empirical evidence contrasts with the wider narrative that farmers are slower at using new technology. This research found that some are slower because it does not align with their strategy. However, sometimes digitalisation aligns with their strategy during external changes, in which case the diversifiers are quick to act.

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

This paper aims to derive a reduced-order model for the heat transfer across the interface between a millimetric thermocapillary liquid bridge from silicone oil and the surrounding ambient gas.

Numerical solutions for the two-fluid model are computed covering a wide parametric space, making a total of 2,800 numerical flow simulations. Based on the computed data, a reduced single-fluid model for the liquid phase is devised, in which the heat transfer between the liquid and the gas is modeled by Newton’s heat transfer law, albeit with a space-dependent Biot function Bi(z), instead of a constant Biot number Bi.

An explicit robust fit of Bi(z) is obtained covering the whole range of parameters considered. The single-fluid model together with the Biot function derived yields very accurate results at much lesser computational cost than the corresponding two-phase fully-coupled simulation required for the two-fluid model.

Using this novel Biot function approach instead of a constant Biot number, the critical Reynolds number can be predicted much more accurately within single-phase linear stability solvers.

The Biot function for thermocapillary liquid bridges is derived from the full multiphase problem by a robust multi-stage fit procedure. The derived Biot function reproduces very well the theoretical boundary layer scalings.