To obtain a sustainable competitive advantage and achieve global innovation leadership, firms in China and other emerging economies must develop strong indigenous innovation capabilities through the coevolution of strategy, organization, resources, and culture. Drawing on current innovation management theories and practices, this study proposes four systematic paths for improving firm innovation systems (FISs), namely, the R&D-based internal collaborative FIS, the strategic vision-driven FIS, the open and user-driven FIS, and the holistic ecosystem-driven FIS. This study contributes to the systematic approach for enhancing corporate indigenous innovation capability based on FISs. Moreover, this study provides theoretical and practical insights for China as well as other developing countries to cultivate world-class enterprises and build an innovative nation.
This study provides a critical review of the concepts of Agile, Lean, Scrum, and Last Planner® System (LPS). A comparative analysis is conducted between LPS and Scrum to expand LPS by considering Scrum’s best practices. Eight dimensions, namely, 1) origins, 2) main purpose, 3) overall system/framework process, 4) tools or artifacts maintained by the team, 5) team composition and main roles, 6) regular events or team meetings, 7) metrics/dashboards, and 8) approach to learning, are evaluated. After analyzing side by side the eight dimensions, it was found that many aspects from Scrum already exist in LPS in the same or similar form. However, the authors identify four main elements from Scrum that can be leveraged to improve the LPS benchmark, such as considering the Scrum “Increment” concept into LPS, having a clear definition of roles and responsibilities, or adding an equivalent to a Scrum Master to have a designated “rule keeper” in LPS. These opportunities to be considered in new LPS benchmarks need to be tested and validated with real applications. To the best of the authors’ knowledge, this work is the first to comprehensively compare Scrum (Agile) and LPS (Lean) and could be seen as a contribution toward the evolution of the Last Planner System for the academic and industrial environments.
The management of resources has been claimed to be as important as scheduling methods. Inefficiency in managing resources may bring about severe delays and cost overruns caused by resource shortages in some cases and/or idle resources in others. Therefore, resources should be utilized efficiently to prevent project failures. Resource leveling is one of the approaches that are used for the management of resources. It aims to minimize fluctuations, peaks, and valleys in resource utilization without changing the completion time of a project and the number of resources required. Although the main principle behind traditional resource leveling is achieving an even flow of resources while the original project duration remains unchanged, the literature supports the need to develop an efficient model that discriminates among the activities that are selected for participation in resource leveling. For this purpose, this study has developed a model that considers the float consumption rates of activities in resource leveling. The float consumption rate is the percentage that is set to determine the maximum amount of float which will be consumed to shift the start time of the activity. The proposed model allows a scheduler to assign float consumption rates to each activity that can be used during the resource leveling procedure. When the required information is inputted, the proposed model automatically changes the required daily resources as it shifts the noncritical activities along their available total float times. The proposed model is expected to minimize the likelihood of severe delays and cost overruns. The model is demonstrated by constructing a network and its resource utilization histograms.
Grand infrastructure projects, such as dam, power plant, petroleum, and gas industry projects, have several contractors working on them in several independent sub-projects. The concern of reducing the duration of these projects is one of the important issues among various aspects; thus, our aim is to fulfill the requirements by using the game theory approach. In this study, a mixed-integer programming model consisting of game theory and project scheduling is developed to reduce the duration of projects with a minimum increase in costs. In this model, two contractors in successive periods are entered into a step-by-step competition by the employer during dynamic games, considering an exchange in their limited resources. The optimum solution of the game in each stage are selected as the strategy, and the resources during the game are considered to be renewable and limited. The strategy of each contractor can be described as follows: 1) share their resources with the other contractor and 2) not share the resources with the other contractor. This model can act dynamically in all circumstances during project implementation. If a player chooses a non-optimum strategy, then this strategy can immediately update itself at the succeeding time period. The proposed model is solved using the exact Benders decomposition method, which is coded in GAMS software. The results suggest the implementation of four step-by-step games between the contractors. Then, the results of our model are compared with those of the conventional models. The projects’ duration in our model is reduced by 22.2%. The nominal revenue of both contractors has also reached a significant value of 46078 units compared with the relative value of zero units in the original model. Moreover, we observed in both projects the decreases of 19.5%, 20.9%, and 19.7% in the total stagnation of resources of types 1, 2, and 3, respectively.
System reliability optimization problems have been widely discussed to maximize system reliability with resource constraints. Birnbaum importance is a well-known method for evaluating the effect of component reliability on system reliability. Many importance measures (IMs) are extended for binary, multistate, and continuous systems from different aspects based on the Birnbaum importance. Recently, these IMs have been applied in allocating limited resources to the component to maximize system performance. Therefore, the significance of Birnbaum importance is illustrated from the perspective of probability principle and gradient geometrical sense. Furthermore, the equations of various extended IMs are provided subsequently. The rules for simple optimization problems are summarized to enhance system reliability by using ranking or heuristic methods based on IMs. The importance-based optimization algorithms for complex or large-scale systems are generalized to obtain remarkable solutions by using IM-based local search or simplification methods. Furthermore, a general framework driven by IM is developed to solve optimization problems. Finally, some challenges in system reliability optimization that need to be solved in the future are presented.
Performance measurement (PM) generates useful data for process control, facilitates communication between different sectors, and helps to align efforts on the most important aspects of the business. Thus, PM plays a key role in the management of projects and organizations. PM is also important in the implementation of lean production principles and methods, such as reducing the share of nonvalue-adding activities, increasing process transparency, building continuous improvement into the process, and benchmarking. Moreover, the adoption of the lean production philosophy requires changes in PM. Despite its importance, limited studies have been conducted on the use of PM systems for assessing the impact of lean production programs in construction projects. In addition, studies on how lean companies (or projects) use performance measurement and to what extent the indicators adopted reflect the result of actions that have been undertaken are limited. This study proposes a set of requirements in PM systems of construction projects from the perspective of lean production and a taxonomy of performance metrics for lean production systems. Five empirical studies have been carried out on construction companies from South America involved in the implementation of lean production systems. The scope of this investigation is limited to the construction projects as production systems rather than PM at the level of construction organizations.
Synchronous collaboration sessions within the context of 4D BIM position construction professionals into a complex socio–technical system. This system includes hardware, software, people, and broader community aspects. This article strictly focuses on the ontology representation of synchronous collaboration sessions with collocated collective decision-making. The model is designed by considering various 4D BIM model uses while a digital multiuser touch table facilitates the collaboration between actors. The outlined ontological model aims to improve interoperability and to move toward a knowledge-driven, smart-built environment paradigm. A knowledge engineering methodology is outlined, by virtue of which the semantics of the presented model are defined and discussed. Concepts from nearby knowledge fields, especially from the Industry Foundation Classes, are reused. Several examples on querying the knowledge base according to the project meeting requirements are outlined to demonstrate the benefits of using the model. Although 4D BIM model data can be imported by using standard formats, capturing data about the social context remains a challenge in the future. This is expected to change the ontology model structure by considering user ergonomics, data modeling requirements, as well as technical implementation constraints.
Blockchain, a peer-to-peer, controlled, distributed database structure, has the potential to profoundly affect current business transactions in the construction industry through smart contracts, cryptocurrencies, and reliable asset tracking. The construction industry is often criticized for being slow in embracing emerging technologies and not effectively diffusing them through its supply chains. Often, the extensive fragmentation, traditional procurement structures, destructive competition, lack of collaboration and transparency, low-profit margins, and human resources are shown as the main culprits for this. As blockchain technology makes its presence felt strongly in many other industries like finance and banking, this study investigates the preparation of construction supply chains for blockchain technology through an explorative analysis. Empirical data for the study were collected through semi-structured interviews with 17 subject experts. Alongside presenting a strengths, weaknesses, opportunities, and threats analysis (SWOT), the study exhibits the requirements for and steps toward a construction supply structure facilitated by blockchain technology.
China is an early user of geothermal energy, and its direct use ranks first in the world. Recent national strategies and policies have enabled China’s geothermal energy industry to enter a new era with important development opportunities. This paper investigates the strengths, weaknesses, opportunities, and threats (SWOT) to China’s geothermal energy industry from political, economic, social, and technological (PEST) perspectives. SWOT–PEST analysis indicates that the resources, market, and technological foundation exist for the large-scale development of China’s geothermal energy industry. However, it experiences constraints, such as unclear resource distributions, incomplete development of government regulations, incomplete implementation of national policies, unclear authority between governmental administrative systems, and lack of uniform technical standards and codes. Therefore, future development strategies have been proposed to provide technical support and policy tools for geothermal energy development. The recommendations to ensure its healthy and sustainable development include improving resource exploration, rationalizing administration systems, enhancing policy guidance and financial support, and cultivating geothermal talent.
This review aims to gain insight into the current research and application of operational management in the area of intelligent agriculture based on the Internet of Things (IoT), and consequently, identify existing shortcomings and potential issues. First, we use the Java application CiteSpace to analyze co-citation networks in the literature related to the operational management of IoT-based intelligent agriculture. From the literature analysis results, we identify three major fields: (1) the development of agricultural IoT (Agri-IoT) technology, (2) the precision management of agricultural production, and (3) the traceability management of agricultural products. Second, we review research in the three fields separately in detail. Third, on the basis of the research gaps identified in the review and from the perspective of integrating and upgrading the entire agricultural industry chain, additional research directions are recommended from the following aspects: The operational management of agricultural production, product processing, and product sale and after-sale service based on Agri-IoT. The theoretical research and practical application of combining operational management theories and IoT-based intelligent agriculture will provide informed decision support for stakeholders and drive the further development of the entire agriculture industry chain.