Keywords

1 Introduction

Agility is becoming increasingly vital for all businesses in today’s highly competitive and consistently changing economic landscape. Organizational agility (OA) has emerged as one of the valuable organizational paradigms managers should follow to generate sustainable competitive advantages and as a critical business success factor (Teece et al. 2016). An increasing number of researches show that business enterprise and R&D investments improve innovation; however, a recent study emphasizes the importance of OA in driving corporate innovation and competitiveness (Franco & Landini 2022). In addition, Sherehiy et al. (2014) address that for a few decades, academia and industry have been concerned with how organizations can effectively adapt to unpredictable, dynamic, and continually changing surroundings. Nevertheless, there were minimal empirical studies on the relationship between agile organizations and agile workforce behavior as drivers of innovation. According to Breu et al. (2002), the success of an agile organization results from the strategic application of individual competencies and behavior toward agility. Nevertheless, no studies have examined workforce agility (WA) from an attitude perspective, showing people’s intention to behave agilely (Asari et al. 2014).

Moreover, there is less attention to the significance of WA as a driver of organizational innovation success, even though it is an essential organizational dimension (Franco & Landini, 2022). The impact of WA on organizational innovation performance has received less research attention in the manufacturing industry (Franco & Landini 2022). As a result, this study aims to view different frameworks related to agility and workforce behavior in originations. Also, to understand how organizational innovation performance in manufacturing enterprises correlates to WA. Studying the impact of WA in agile manufacturing on innovative organizational performance, it provides insights into how these enterprises’ employees’ capabilities may affect their agile behavior to remain competitive in the dynamic markets.

To address this gap, the paper investigates the relationship between workforce behavior toward agility as a critical component of OA to improve organizational innovation performance and sustain competitive advantage. Therefore, the paper attempts to address the below research questions:

  1. (1)

    What are the different interrelated frameworks and research models related to agility in organizations, the workforce, and the manufacturing sector?

  2. (2)

    What is the impact of workforce agile behavior in agile organizations on their innovative performance in the manufacturing sector?

The paper will review the literature on agility frameworks, OA, the agile behavior of the workforce, agile manufacturing, and organizational innovation performance. Then, the theoretical framework related to the topic will be explained and linked to the selected variables, followed by the hypothesis related to the research model.

2 Theoretical Background

2.1 Overview of Agility Frameworks, Agile Organizations, and Agile Manufacturing

Several academics established frameworks and models to examine agility and its features in various contexts to adapt to the market’s quick change. As a result, these frameworks and models range in content and structure, which leads to organizationally distinct definitions of agility (Zitkiene & Deksnys 2018). According to the review of previous research on agility by Wendler (2013), it is claimed that there is no consensus regarding this concept definition, which leads to limitations and challenges in executing large-scale empirical research concerning different contexts or fields. The scholar categorized agility frameworks into four domains. The first two can align with industry and technology (agile manufacturing, agile software). The second one is related to organization and human resource management ( agile workforce and agile organization which receive less attention than the rest. Agility frameworks share important organization management concepts like organizational culture, workforce, capabilities, and technology.

However, there is less research on integrating and developing an integrated and holistic agile enterprise concept, including more than one domain. Although enterprise agility started with agile manufacturing idea creation, OA received the most interest lately once agile software development got recognition. Consequently, this illustrates the rising interest in agility’s impacts on the entire organization, not just functional or structural areas (Wendler 2013). Zitkiene & Deksnys (2018) developed an OA model based on the most thorough and comprehensive framework of agile manufacturing proposed by Sharifi et al. (2001) to evaluate OA after intensive research and systematization of the literature on this topic. The framework combines agility drivers, enablers, capabilities, and practices sustaining competitive advantage in today’s dynamic market. Organizational adaptability begins with identifying and implementing agility drivers. After recognizing the change, decision-makers should assess the situation. After creating the inventory, company decision-makers should use enablers and capabilities to adapt to environmental factors. The outcomes create new products and practices to alter operations for the best innovation and results.

Sherehiy et al. (2014) suggest more review and attention to organizational flexibility and workforce adaptability research in industrial and organizational mindset or organizational growth and behavior. So, the ability of an organization to quickly and effectively shift its resources to higher-yielding activities that create and protect value for environmental factors can describe OA (Teece et al. 2016). Therefore, the dynamic capabilities framework is frequently utilized in OA because it illustrates interrelationships that managers must understand to establish and maintain competitive advantage. It aids in setting priorities and ensures alignment between the organization’s strategy, structure, and operating environment. Sensing, seizing, and transformation are the three essential dynamic characteristics that organizations need to be agile. Sensing entails recognizing changes in the market and environment, grabbing new possibilities, and transforming entails altering organizational procedures and structures to accommodate the shifting environment (Teece et al. 1997).

2.2 Workforce Agile Behavior and Manufacturing Sector

To better understand the impact of agility in organizations and WA, researchers try to understand and define the relationship between them. According to Breu et al. (2002), WA is recognized in the early 2000s by focusing on two main dimensions (speed and flexibilityThe concept of agility includes both adaptability and flexibility as qualities, and agile organizations incorporate all core elements from the concepts of adaptable and flexible organizations. Abrishamkar et al. (2021) examine the extent to which the new innovation of products favorably affects the link between WA, which raises the possibility of businesses becoming top performers in the high-tech manufacturing sector of a developing economy. WA is necessary for organizational and manufacturing agility. Raisch & Birkinshaw (2008) demonstrate that agility in the workplace is the individual’s ability to rapidly and successfully adapt to new situations. On the other hand, Franco & Landini (2022) explain WA as an organization’s ability to reallocate resources quickly and effectively from non-value-adding tasks to those that create value, emphasizing innovative resolutions to challenges.

Sherehiy et al. (2014) illustrate that successful businesses in unpredictable business environments need WA in their WA model. Also, WA implies a workforce with three essential factors (proactivity, flexibility, and resilience) in handling unplanned and unusual situations. These characteristics are the main components of WA since it is empirically proven to positively impact new product innovation in the manufacturing sector in Iran (Abrishamkar et al. 2021). Similarly, A study of several Indian industries, including those in the manufacturing and service sectors and the public and private sectors, indicated that agile organizational strategies and practices that support WA could improve the agile characteristics and behavior of the workforce (Muduli 2016). Previous scholars used different frameworks to support their research, like the dynamic capabilities framework and theory of planned behavior (PBT). Alavi & Wahab (2013) divide the study in this area into two groups (agile manufacturing models and practices reaches) and suggest future research to look at the influence of WA on the behavior of organizations and employee performance. Ajgaonkar et al. (2021) view WA as a high-level approach under the dynamic capabilities framework since they develop a conceptual model heuristically of WA drivers connected with the framework components. Sensing, seizing, and constant renewal help organizations make decisions including relocation of external and internal human resources. According to Tessarini Junior & Saltorato (2021), relatively few empirical studies have been done, making it difficult to arrive at a single definition and classification for WA. Moreover, a theoretical model is developed for an agile workforce based on Ajzen’s theory of planned behavior (TPB) to examine the relationship between agility and workforce attitude/behavior using TPB (Asari et al. 2014). TPB shows how attitudes, subjective norms, and perceived behavioral control affect people’s actions, improving understanding and predicting human behavior (Ajzen 1991). However, the theoretical model proposed by Asari et al. (2014) is not empirically tested despite the significant study analysis. This paper will use the TPM to explore the impact of workforce agile behavior of manufacturing enterprises on innovative performance.

2.3 Agility and Organizational Innovation Performance

Research on innovation generally agrees that it is the main driver of economic growth, competitive advantage, the industrial revolution, and public service highly requires innovation practices (Evangelista & Vezzani 2010). Cai et al. (2019) argue that the ability to innovate depends on the availability of human resources that may be redirected or reassigned to assist organizations that develop new products or services. Thus, Franco & Landini (2022) investigate how WA can influence innovative performance as a distinct component of the organization’s success. Also, the agility of the workforce is a critical aspect in triggering behavioral motivations to perform innovatively, which positively influences product and process innovation. According to Yildiz & Aykanat (2021), innovation is the best way for businesses to adapt to quickly changing circumstances in complex structures. The scholars suggest splitting technical (new products, new manufacturing) and non-technical (new marketplaces, new approaches of organization) structures to eliminate the complexity and achieve the desired innovative performance. The scholars’ research shows that organizational innovation is crucial in the relationship between agility and firm performance since it directly impacts the business’s performance and adaptability to changing conditions. Nevertheless, the literature on organizational innovation is limited compared to other types of innovation despite its importance and the focus on technology and process innovation. (Phan 2019). For example, an empirical study showed that firm agility significantly mediates the link between big data analysis use and innovation performance (ZareRavasan 2021).

3 Theoretical Framework

After reviewing the literature on the most relevant theoretical framework related to the research topic, this paper mainly utilizes TPB as the theoretical framework to study the impact of agile behavior manufacturing enterprise workforce on organizational innovation. The first factor of TPB influencing behavior is an individual’s intentions, which represent their readiness to engage in a particular behavior. The subjective norm is the second one, and it expresses the subjective experience of social pressure to engage in or abstain from the behavior. Perceived behavioral control, which measures how much one believes behavior is under their control, is the third factor that influences intentions (Ajzen 1991). Several researchers extend the TPB to investigate individuals’ intentions and organizational behaviors. Moreover, Jimmieson et al. (2008) argue that the researchers can utilize the framework to understand better the antecedents of employees’ intentions to support an organizational change event behaviourally and decide if a behavior will be taken in response to market changes. Therefore, the three factors of TBA can predict employee support for organizational changes in the surrounding landscape to sustain competition.

Agile behaviors consider deliberate action based on a personal objective of the workforce; consequently, internal and external perceived control impacts it. The behavioral components of agility, such as flexibility and adaptation, have received much attention in WA research (Asari et al. 2014). Furthermore, the absence of flexible resources and competencies might hinder achieving agility in organizations. WA is a component that demonstrates how the workforce will behave in the workplace at the time of change through specific factors such as proactivity, adaptability, and resilience (Milicevic et al. 2022). Yildiz & Aykanat (2021) highlighted it has been demonstrated empirically that speeding up the introduction of new innovation (products and services) by organizations has a beneficial impact on their ability to perform effectively. Also, agility allows enterprises to respond swiftly to market variations by modifying the amount of items supplied, how often new models are promoted, and the number of new products released. To be able to provide a conclusive response to the paper questions, the impact of workforce behavior toward being agile in dynamic using the three factors will be studied.

4 Research Model

This paper suggests a research model based on TPA since the model offers the theoretically relevant foundation for devolving propositions that support the research variables. The proposed model focuses on the relationship between the behavior of the workforce toward agility (proactivity, adaptability, and resilience) and the innovative performance of manufacturing enterprises (product and process innovation). Because agility illustrates how organizations use speed, flexibility, innovation, and quality to compete, it may assist them in using flexible resources and best practices to deliver client-driven goods and services in a fast-changing environment (Yusuf et al. 1999). Breu et al. (2002) address a significant gap in the research on agility by delivering the first empirical study to analyze the impact of OA pressures on the workforce. Agility studies used adaptive and flexible organization concepts and approaches yet lacked essential organizational and management enhancements, such as human resources.

Most of the research on WA has focused on the effects of training and incentives on employee behavior. However, there is limited research on the causes and impact of this field (Sherehiy et al. 2014). Proactivity describes a circumstance in which an individual promotes actions that have a favorable effect on a modified environment. According to Sherehiy et al. (2014), Adaptability in business is the ability to follow many companies’ plans and tactics while quickly switching from one work, job, or strategy to another. These techniques must deviate to the extent that it does not jeopardize the organization’s integrity or fundamental objectives. So, to execute several duties, switch between roles with ease, and work concurrently on many tasks in various teams, manufacturing businesses must have a workforce with flexible behavior. The capacity for a person to perform under persistent stress despite significant changes in the workplace is known as resilience. As a result, individuals exhibit a positive attitude toward changes, innovative ideas, technology, and a capacity for managing stress (Milicevic et al. 2022). Thus, the following hypotheses are suggested based on these arguments:

  • H1a: Workforce proactivity behavior positively impacts manufacturing enterprises’ product and process organizational innovation.

  • H1b: Workforce adaptability behavior positively impacts manufacturing enterprises’ product and process organizational innovation.

  • H1c: Workforce resilience behavior positively impacts manufacturing enterprises’ product and process organizational innovation.

The relationship between workforce agile behavior in agile organizations on their innovative performance in the manufacturing sector is represented in Fig. 1.

Fig. 1.
figure 1

The Research model representation

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5 Discussion and Conclusion

The paper investigates the existing literature on agility in general and agile WA factors (proactivity, adaptability, resilience) that can impact agile manufacturing enterprises’ product and process innovation. The selected WA factors result from agile intentions and behavior based on the TPB. It contributes to the body of knowledge by examining the nature of this relationship and linking the selected variables to the existing literature since there is limited focus on studying the impact of agile behavior on the workforce. Moreover, the suggested hypotheses can prove the degree of the positive correlations between WA and the desired organizational innovative performance. As a result, an agile workforce can adapt more quickly to shifting markets and help accelerate the development of new products, services, and business models. The model can be empirically studied in future research to enhance the knowledge of agility. The proposed research model can be empirically tested with selected intervening variables, such as the sizes and ages of enterprises in the manufacturing sector in diverse regions of the world. The study can be conducted to examine the impact of agile behavior on employees’ and organizations’ innovative performance in the public sector. Also, the research model hypothesis can be extended to investigate the effect of intention to agility on organizational innovative performance. The result can help leadership create more comprehensive knowledge of the workforce’s characteristics and traits to help with strategic agility planning, especially during a crisis.