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This study aims to emphasize the integration of lean start-up and design thinking approaches and investigate how they may be used together.

The report uses a systematic literature review methodology to analyze and summarize previous research on combining lean start-up and design thinking. Inferences were discovered and analyzed after relevant publications were chosen based on predetermined inclusion criteria.

The research shows that combining lean start-up and design thinking significantly impacts entrepreneurship. Start-ups can efficiently uncover consumer needs, reduce risks and improve their product or service offerings by combining the client-centricity of design thinking with the iterative and data-driven concepts of lean start-up. This integration promotes an innovative culture, gives teams the freedom to try new things and learn from mistakes and raises the possibility of start-up success.

The dependence on pre-existing literature, which might cover only some potential uses and circumstances, is a weakness of this research. It is advised that more empirical research be conducted to determine the precise circumstances in which the integrated strategy performs best. Future studies should also explore the difficulties and drawbacks of using these approaches to offer suggestions for overcoming them and maximizing their advantages.

The findings have significant ramifications for business owners and other professionals working in the start-up environment. The combination of lean start-up and design thinking emphasizes the relevance of early customer interaction and empathy-driven design. To foster creativity and hasten the expansion of start-ups, practitioners are urged to create a comprehensive strategy that integrates the advantages of both techniques. Through this integration, business owners may develop solutions that appeal to their target market, increasing adoption rates and market competitiveness.

This study is interesting in comparing lean start-up and design thinking, emphasizing the overlaps and benefits of their application to entrepreneurship. This study discusses successful start-up methods by offering suggestions for future research and practice. It also provides a basis for further developing and adopting the integrated approach.

Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.

The authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.

The results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.

The paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.

Examining the role of women on board (WoB) toward corporate sustainable growth (CSG) through leverage policy (LP). This research also investigates the interaction effect of WoB and LP on improving CSG.

This study uses a moderated mediation model to examine the impact of WoB on CSG, mediated by LP. Data from 48 KEHATI IDX ESG Sector Leaders Index companies observed from 2015 to 2021 were analyzed using the structural equation model partial least square (SEM-PLS) Warp.PLS 8.0. The research applies instrumental variables (IV) to test and control endogeneity due to nonrandom sample selection.

We found evidence that LP acts as a full mediator between the presence of WoB and CSG. The presence of WoB plays a moderate role by slightly weakening the influence of LP on CSG. Furthermore, we obtained evidence showing that the relationship between WoB and CSG is J-curve-shaped, a nonlinear relationship related to critical mass. Where the WoB ratio is at least 8.35% or higher, it will increase CSG in companies that have implemented the concept of environment social governance (ESG) in Indonesia.

This model uses a moderated mediation model and J-curve analysis; there is an interaction between WoB and LP on different paths of the mediator to CSG. This model examines the role of WoB as a moderator of the effect of LP on CSG. A nonlinear J-curve test was conducted to determine the minimum level of WoB that can influence the increase of CSG.

The purpose of this paper is to systematically review the history and current state of lesson study (LS) in Germany. In particular, this paper describes the development of LS over time and its stakeholders.

Conducting a systematic literature review, we searched three scientific databases and Google Scholar, examined 806 results and included 50 articles in our final sample, which we analyzed systematically.

The spread of LS in Germany can be divided into three phases, characterized by their own LS projects as well as their own ways of understanding LS. Although interest in LS has increased significantly in recent years, it is only present at a small number of schools and universities in Germany if compared internationally. Furthermore, this paper identifies the so-called learning activity curves as a tool frequently used for observation and reflection that appears to be unknown outside German-speaking countries.

This paper may act as an outline for countries without large-scale LS projects and with limited support from policymakers. The experience from Germany demonstrates the outcomes and challenges that can arise in such a situation and shows how unique LS features and proceedings have emerged.

The purpose of this study is to investigate the impact of COVID-19 on some fiscal and monetary indicators in the Kingdom of Saudi Arabia.

The research relied on data, studies and reports issued by the International Monetary Fund, Arab Monetary Fund, Saudi Central Bank, Investing Website and the World in Data Website.

Many sectors have been affected by the COVID-19 pandemic, which outbreak has been associated with a high cost, in addition to increased inflation and prices, a result that was confirmed by the increase in consumer price indices for different sectors. The general consumer price index for the second period rose above that of the first period, while an upward shift occurred in the curve depicting the Saudi Riyal exchange rate against the United States (US) dollar during the second period above that of the first period, only in slope, due to outbreak of the pandemic. Impact of the number of daily new cases infected with COVID-19 was the highest on the opening and closing price indices of the food retail sector, the pharmaceutical sector and the transportation sector; while impact of the number of daily deaths by COVID-19 was the highest on the opening and closing price indices of the banking sector, the general index and the investment and finance sector. In addition, impact of the daily reproduction rate of COVID-19 was the highest on the opening price indices of the energy sector, the food production sector and the transportation sector.

The research aims to demonstrate measures taken by the Kingdom of Saudi Arabia through fiscal and monetary policies.

The COVID-19 pandemic is still an ongoing global pandemic. The virus was first identified in Wuhan City in China at the beginning of December 2019. At the end of January 2020, the World Health Organization (WHO) declared that the outbreak of the virus represented a public health emergency, and later, on March 11, 2020, WHO declared the situation had transformed into a pandemic. Until January 17, 2022, the pandemic had caused more than 328 million cases and 545 million deaths, while 188 million of the cases had recovered. It is worth mentioning that the pandemic caused several social and economic disruptions, including a global economic recession; shortages in goods, supplies and equipment due to consumers' panic and thus tendency to buy; besides causing other disruptions like the negative impacts on health, as well as political, cultural, religious and sport events that influenced economic policies, including both the fiscal and monetary policies of world countries (Wikipedia, 2022).

Social implications steps that taken to reduce the impacts of the COVID-19 pandemic, in addition to measuring the impacts of the COVID-19 pandemic (as the main event next to which other events fade up) on some of the fiscal and monetary indicators for the Kingdom of Saudi Arabia.

The research aims to demonstrate measures taken by the Kingdom of Saudi Arabia through fiscal and monetary policies to mitigate the impacts of the COVID-19 pandemic, in addition to measuring the impacts of the COVID-19 pandemic (as the main event next to which other events fade up) on some of the fiscal and monetary indicators for the Kingdom of Saudi Arabia.

Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.

Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.

In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.

The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.

Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

This study aims to investigate the impact of local windfall gains from the Spanish Christmas lottery on household consumption behavior.

The study applies differences-in-differences to assess permanent income hypothesis (PIH) validity, examining pre- and postlottery consumption effects. Additionally, it also uses an instrumental variable regression, using the lottery shock as an instrument for total expenditures, to estimate the Engel curves.

The paper finds a PIH violation; households in winning region notably increase consumption on durable and nondurable goods compared to nonwinning ones. Moreover, durable goods consumption is responsive to lottery winnings, while nondurable goods consumption are unit-elastic to expenditure shocks.

To the best of the author’s knowledge, this is the first paper analyzing the effects of winning regions of the Spanish Christmas lottery in all types of consumption goods, testing its consequences in the PIH and estimating its effects in the Engel curves.

Using real-time support systems may help operators in road construction to improve paving and compaction operations. Nowadays, these systems transform from descriptive to prescriptive systems. Prescriptive or operator guidance systems propose operators actionable compaction strategies and guidance, based on the data collected. It is investigated how these systems mediate the perceptions and actions of operators in road pavement practice.

A case study is conducted on the specific application of an operator guidance system in a road pavement project. In this case study, comprehensive information is presented regarding the process of converting input in the form of data from cameras and sensors into useful output. The ways in which the operator guidance systems translate data into actionable guidance for operators are analyzed from the technological mediation perspective.

Operator guidance systems mediate actions of operators physically, cognitively and contextually. These different types of action mediation are related to preconditions for successful implementation and use of these systems. Coercive interventions only succeed if there is widespread agreement among the operators. Persuasive interventions are most effective when collective and individual interests align. Contextual influence relates to designs of the operator guidance systems that determine human-technology interactions when using them.

This is the first study that analyzes the functioning of an operator guidance system using the technological mediation approach. It adds a new perspective on the interaction between this system and its users in road pavement practice.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.