1- Introduction

2- Literature review

3- Research methodology

4- Results, analysis, and discussion

5- Concluding remarks, limitations, and future research

References

Abstract

Little is known about the effects of lean manufacturing practices on the process innovation performance of manufacturing organisations. This research aims to fill this gap and explore the aforementioned interdependency. A research framework consisting of 22 measurement scales and three pairs of hypotheses was developed based on an extensive literature review. A large-scale self-administered questionnaire was distributed among appropriately selected industrial experts. Datasets obtained from 340 usable responses were analysed through confirmatory factor analysis, descriptive statistics, correlations, and multiple linear regression models. The findings suggest that both technical and human lean practices have a moderate to strong positive impact on the input and occurrence of incremental and radical process innovation in manufacturing organisations. In turn, as an output of process innovation, this appears to enhance companies’ operational performance. Thereby, the results dispel the scholarly and managerial misconception that LM and innovation are difficult to coexist.

Introduction

Over the last 30 years, lean manufacturing (LM) has provided some of the most popular and effective practices and tools for striving towards operational excellence (Albliwi, Antony, & Lim, 2015). In essence, LM aims to eliminate any non-value-adding activities through continuous incremental improvements (Abolhassani, Layfield, & Gopalakrishnan, 2016). Global megatrends have accelerated the pace of technological developments, increasing the importance of dynamic operations (Westkämper, 2014). In this environment, merely optimising the exploitation of innovation is not enough. Companies are challenged to enhance their explorative innovation capabilities to ensure sustainable competitive advantages (Chen & Huang, 2009; Kafetzopoulos, Gotzamani, & Gkana, 2015). In addition to managing existing products and services, they must incrementally and radically innovate in technology and processes to outpace global competition (Westkämper, 2014). On one hand, exploitation and exploration seem contradictory (Berente & Lee, 2014; Jones & Linderman, 2014; Pakdil & Leonard, 2017). By principle, standardised lean environments appear to be the opposite of increased worktime flexibility and colourful creativity rooms. Similarly, structured and streamlined workflows associated with LM seemingly contradict the need of freedom to innovate. Pakdil and Leonard (2017) outline a paradox of LM: while employees are encouraged to continuously innovate autonomously, guidelines and work regulations provide strict rules for their operations. Spear and Bowen (1999) also describe the Toyota Production system as a paradox between rigid processes and flexible responsiveness. Jones and Linderman (2014) call this a trade-off between innovation and efficiency of manufacturing plants. However, LM is centred on improvement (Jasti & Kodali, 2015), and increasing innovativeness is occasionally presented as an important mechanism for LM (Lyons, Vidamour, Jain, & Sutherland, 2013). In addition, various human resource (HR) oriented LM practices (e.g. diverse training, teamwork, and flatter hierarchies) (Olivella, Cuatrecasas, & Gavilan, 2008) are often listed among general attributes of innovation fostering environments (Dul & Ceylan, 2014; Fiates, Fiates, Serra, & Ferreira, 2010). Together, the outlined contradictions raise the question as to whether, and in which way, the implementation of LM affects the ability of manufacturing organisations to generate process innovations.

Little is known about the effects of lean manufacturing practices on the process innovation performance of manufacturing organisations. This research aims to fill this gap and explore the aforementioned interdependency. A research framework consisting of 22 measurement scales and three pairs of hypotheses was developed based on an extensive literature review. A large-scale self-administered questionnaire was distributed among appropriately selected industrial experts. Datasets obtained from 340 usable responses were analysed through confirmatory factor analysis, descriptive statistics, correlations, and multiple linear regression models. The findings suggest that both technical and human lean practices have a moderate to strong positive impact on the input and occurrence of incremental and radical process innovation in manufacturing organisations. In turn, as an output of process innovation, this appears to enhance companies’ operational performance. Thereby, the results dispel the scholarly and managerial misconception that LM and innovation are difficult to coexist.

Introduction

Over the last 30 years, lean manufacturing (LM) has provided some of the most popular and effective practices and tools for striving towards operational excellence (Albliwi, Antony, & Lim, 2015). In essence, LM aims to eliminate any non-value-adding activities through continuous incremental improvements (Abolhassani, Layfield, & Gopalakrishnan, 2016). Global megatrends have accelerated the pace of technological developments, increasing the importance of dynamic operations (Westkämper, 2014). In this environment, merely optimising the exploitation of innovation is not enough. Companies are challenged to enhance their explorative innovation capabilities to ensure sustainable competitive advantages (Chen & Huang, 2009; Kafetzopoulos, Gotzamani, & Gkana, 2015). In addition to managing existing products and services, they must incrementally and radically innovate in technology and processes to outpace global competition (Westkämper, 2014). On one hand, exploitation and exploration seem contradictory (Berente & Lee, 2014; Jones & Linderman, 2014; Pakdil & Leonard, 2017). By principle, standardised lean environments appear to be the opposite of increased worktime flexibility and colourful creativity rooms. Similarly, structured and streamlined workflows associated with LM seemingly contradict the need of freedom to innovate. Pakdil and Leonard (2017) outline a paradox of LM: while employees are encouraged to continuously innovate autonomously, guidelines and work regulations provide strict rules for their operations. Spear and Bowen (1999) also describe the Toyota Production system as a paradox between rigid processes and flexible responsiveness. Jones and Linderman (2014) call this a trade-off between innovation and efficiency of manufacturing plants.

1- INTRODUCTION

2- EXPLAINING THE SOCIAL PERFORMANCE OF LEAN PRODUCTION

3- THE TWO CONTEXTS UNDER STUDY

4- RESEARCH DESIGN AND METHOD

5- TRADITIONAL EMPLOYMENT ARRANGEMENTS

6- DISTINCTIVE EMPLOYMENT ARRANGEMENTS

References

ABSTRACT

Several studies have acknowledged that lean production is implemented in diverse ways across workplaces, thereby generating different outcomes for workers. However, explanations for this variability needs further development. The present article addresses this issue by considering the role played by workplace unions’ framing of lean production. It finds that unions’ framing is derived from their identities in interaction with available resources in institutional and organisational terms. A case study comparison of the automotive parts industry in Italy and the United States was conducted.

INTRODUCTION

Lean production constitutes a diffuse organisational model. While it has been proven capable of increasing companies’ competitiveness (Shah and Ward, 2007), its outcomes for workers, namely, its social performance, remain disputed (Distelhorst et al., 2016). In focusing on organisational and human resource management (HRM) practices, lean production is perceived as representing a bottom-up approach to implementing technical principles and related techniques aimed at improving both the efficiency of production processes and work experience (Shah and Ward, 2007). This approach would encompass the transformation from Taylor-Ford organisational models to the adoption of both distinctive and traditional (but nevertheless differently regulated) employment arrangements (Godard, 2004; Pagell et al., 2014). Indeed, a number of studies have demonstrated that the application of lean production in the field of human capital deployment varies among workplaces. For instance, Adler and Borys (1996) found that in the New United Motor Manufacturing, Inc. auto plant, which was co-founded by Toyota and General Motors and applies lean production principles, workers were considerably more engaged than was the case in traditional Taylor-Ford factories because they were allowed to standardise and formalise the most efficient work procedures by accounting for their working conditions. In contrast, paying attention to the British automotive industry, Stewart et al. (2009) argued that the realities of lean production involved increased production pressures and greater stress. However, the reasons behind this variation and contrasting consequences for workers remain unclear (Bamber et al., 2014).

1- Introduction

2- Literature review

3- Approach

4- Overview of case study

5- Conceptual process mapping

6- Simulation model

7- Application of lean construction principles

8- Conclusions

9- Limitations and future research

References

Abstract

One way to encourage adoption of prefabrication and off-site manufacturing (OSM) techniques, such as modular construction, is to improve the efficiency of site operations, which makes the technology more attractive to non-adopters. Lean principles have been widely applied to improve the productivity and efficiency of construction operations, while simulation augments Lean theory by allowing its benefits and issues to be analyzed quantitatively before actual implementation. Thus, this study aims to conduct a detailed simulation study of modular construction operations, otherwise known as Prefabricated Prefinished Volumetric Construction (PPVC) in Singapore. In contrast with existing research, which are frequently focused on the barriers and drivers to the adoption of prefabrication, this study will provide and evaluate recommendations to improve modular construction efficiency through application of Lean concepts. A detailed baseline (As-Is) simulation model of an ongoing PPVC project case study was first developed. Lean Construction principles were then applied to the baseline simulation model. Key Lean Construction principles and concepts implemented includes Total Quality Management, E-Kanban based Just-In-Time deliveries, cross training and the use of construction robotics. Lean (To-Be) simulation models were developed based on the Lean Construction principles. The outputs from the baseline and Lean models were compared to assess the impact of the proposed improvements. The findings demonstrated that through the application of Lean concepts, reductions in cycle time and process time, and increases in process efficiency and labor productivity can be achieved. The case study also provides a detailed description of the simulation approach, which is a useful reference for future application of simulation in offsite construction research.

Introduction

With its ability to harness the efficiency of manufacturing processes, offsite construction, offsite manufacturing (OSM) or prefabrication, has long been seen as the way forward in enhancing productivity of the construction sector [1–3]. It offers significant benefits, such as reduced project duration and defects, and improved health and safety [2,4]. Modular construction is a subset of OSM, where each prefabricated module is a volumetric component that can be a complete or partial room or unit (e.g. bathroom or lift) [5,6]. In contrast, non-volumetric offsite construction includes two-dimensional elements like walls and columns. Interest in OSM persisted across the years. In the United Kingdom, for example, the OSM sector has seen tremendous growth since the Egan Report (Egan 1999) [7], which recommended OSM as a solution to boost productivity and overcome labor shortages. OSM continues to be highlighted in the “Construction 2025” document [8]. Similarly, the US National Research Council has identified offsite construction as the key to improving the competitiveness of its construction industry [9]. Offsite construction has been used in Singapore since the 1980s. Efforts to increase the use of prefabrication have largely been spearheaded by the Building and Construction Authority (BCA). In 2014, BCA unveiled its Second Productivity Roadmap [10] which aimed to increase the prevalence of Design for Manufacturing and Assembly (DfMA), including the prefabrication of components that can be assembled on site. One of the key technologies promoted in Singapore is Prefabricated Prefinished Volumetric Construction (PPVC), in which building modules complete with internal finishes and fittings are manufactured off-site and assembled on-site in a Lego-like manner. PPVC is essentially modular construction using complete and pre-finished room units. Nonetheless, barriers to prefabrication such as perceived higher capital costs have impeded its adoption [11]. For instance, OSM only contributed to 2.1% of total construction value in the UK in 2007 [12].

1- Introduction

2- Game-based Lean education and training

3- Simulators for game-based Lean education and training

4- Experiences from game-based training of students and industrial workers

5- Suggested directions for developing lean education as a research discipline

References

Abstract

Production simulation games are increasingly popular for training students and industrial employees in Lean Production principles. They range from paper- or desktop-based games to full scale simulators and proper manufacturing machinery. This paper reports on experiences from using both desktop games and a full scale simulator. Desktop games are suitable when training people who already have a fair understanding of lean principles. Shop floor workers usually have difficulties in seeing analogies between desktop games and their work environment. For both students and industrial workers, training effects and immersion tend to be higher when using full scale simulators.

Conclusions

In game-based Lean Production training, it is important to use a training environment that is suitable both for the intended purpose of the training and for the participant group. Simulators must exhibit behavior that is perceived as “natural”. Full-scale simulators have the advantage that they are similar enough to a real work environment to stimulate engagement of the participants whilst still being flexible enough to represent different work environments. In particular industrial workers can benefit from this as they can relate to their work environment. Measurement of Lean Production training effects has been identified as a topic for future work, in particular assessment of training effects on groups or organizations rather than on individuals. Current methods/tools are subjective and not uniform, hence it is proposed that they should be developed by the Lean Educators community as a whole.

In the transition from a traditional mass-production organization to a lean manufacturing (LM) enterprise, transformation in both technical and socio-cultural aspects is needed (Tortorella and Fogliatto, 2014). Since a successful LM implementation is highly dependent on firm employees (Sawhney and Chason, 2005), it is important to comprehend the underlying culture of LM practices (Bhasin and Burcher, 2006). In this context, leaders play a crucial role in the establishment of such lean culture (Mann, 2009; Shook, 2010). Leadership commitment and leader’s communication skills have been highlighted as key managerial attributes for successful LM implementation (Womack and Jones, 2003; Spear, 2004). In this sense, common characteristics of a lean leader are collaboration, delegation, and the ability to motivate employees (Angelis et al., 2011; Pamfilie et al., 2012; Dombrowski and Mielke, 2014; Gelei et al., 2015). Overall, Emiliani and Stec (2005) and Suresh et al. (2012) suggested that lean enterprises need to have transformational leaders at the top, who behave according to expected culture and disseminate the proper lean principles. Although leadership is a highly popular topic in academia, there are still gaps in the literature that must be addressed, in particular in companies that are implementing LM (Marodin and Saurin, 2013; Bortolotti, Boscari and Danese, 2015). Researchers also emphasize the influence of contextual variables on leadership performance, which may hinder or favor their leadership in the shift to a leaner company (Deschamps, 2005; Bäckström and Ingelsson, 2015). For instance, Castka et al. (2001) and Marksberry et al. (2010) indicated that size of the team, evidenced by the number of followers, might be an important contextual variable for determining assertive leadership styles. Parry et al. (2010) and Tortorella et al. (2017) indicated that greater leadership experience, which is closely related with leaders’ age, may entail enhanced interpersonal skills that might favor the leader’s choice for behaviors that more effectively support LM implementation. Thus, we argue that the identification of the contextual variables and leadership styles in an LM implementation could improve the understanding of the difficulties that companies have to implement LM. Therefore, we propose the following two research questions: RQ1. How do different leadership styles favor LM implementation? RQ2. How does context influence the relationship between leadership style and LM implementation? Thus, this paper aims at identifying the relationship between leadership styles and the implementation of LM practices, as well as to analyze the moderating effect of the inherent contextual variables of leadership. We carried out a survey with 225 leaders from different Brazilian companies that are undergoing LM implementation. Respondents were asked to fill three questionnaires in the survey: the implementation level of LM practices, their leadership style and adaptability, which is defined through the application of the situational leadership (SL) questionnaire proposed by Blanchard (2010), and details about contextual variables pointed out in the literature as influential for leadership style adoption.

The manufacturing system output is a function of the whole system, not just individual processes. When we view our system as a whole, we realize that the system output is a function of the weakest link. The weakest link of the manufacturing system is the constraint. Consequently, there needs to be focus on the coordination of efforts to optimize the overall system, not just individual processes [1]. When a system matures in lean implementation, the production flows smoother and the main constraint becomes less obvious. However, the impact of performance of constraining resources in a lean system, especially one with moving assembly lines, is still evident. Because “every value stream has a primary bottleneck (constraint) that limits its ability to reach its goal” [2, p. 175], it is even more critical to be able to identify system constraints in a lean environment. Theory of Constraints (TOC) is a well-known methodology for systems improvement that includes principles and practice guidelines that can be adopted by practitioners [3]. The famous novel for operations management, The Goal, written by Eli Goldratt [4] caught the attention of process improvement professionals and began the use of this methodology. From this book, the five focusing steps (5FS) were brought out: 1) Identify the System Constraint, 2) Decide How to Exploit the Constraint, 3) Subordinate Everything Else, 4) Elevate the Constraint, and 5) Go Back to Step 1, but beware of “Inertia”. The concept of integrating Lean, Six Sigma and the Theory of Constraints is being explored more and more while simultaneously being applied to various industries [5]. The integration of Lean and TOC will be the focus of this manuscript. Constraint identification at a lean manufacturing plant using TOC will be the method of integration. In mass production environments, constraints are usually easy to find; just look for large stockpiles of Work-In Process (WIP), backlogs, and frequent expediting [2]. But in a lean manufacturing environment, none of these conditions should exist; therefore a different approach has to be taken in order to identify the system constraint(s).

1. Introduction

In India the Small Scale Industries (SSE) are producing more than 8000 components and consist of Traditional Cottage & house hold Industries and modern small scale Industries. Out of these units more than 80% are family owned, around 17% are partnership and only 2% are Limited companies. The modern Micro Small Medium enterprises (MSMEs) are incorporating new technology and advanced manufacturing systems in their plants, using information technology to get connected with the world, focused on quality products with variety and changing from the traditional working to a world class manufacturing organizations [3]. The technology gap is alarming and the expenditure on R&D in an Indian Industry is less than 0.6% on average of its turnover as against the world average of 2.5%.the most problem faced by the MSMEs has been in accessing technology and maintaining competitiveness[7,9,10,11]. In this growing competition these MSME‟s focusing on more output without implementing proper tools which is resulting in one of the seven wastages. These wastes can be reduced by implementing lean techniques. Lean Manufacturing is an operational strategy oriented toward achieving the shortest possible cycle time by eliminating waste [14]. It is derived from the Toyota Production System and its key thrust is to increase the value-added work by eliminating waste and reducing incidental work [8]. The technique often decreases the time between a customer order and shipment, and it is designed to radically improve profitability, customer satisfaction, throughput time, and employee morale [1].The main tool in analyzing wastes and time consumption throughout the manufacturing cycle in lean manufacturing is Value stream mapping. A value stream map is typically created as a one-page flow chart depicting the current production path or design path of a product from the customer’s request to delivery [6]. An important goal of value stream mapping is to identify processes that do not provide value so they can be improved. In lean production, value can be thought of as anything the customer is willing to pay for Processes that do not provide value are called waste [2]. Value stream maps document the current state of the value stream as well as the future state of the value stream and define any gaps between the two.

The characteristics of operation management models have evolved over a period to adapt to the new challenges of society. In the beginning of the twentieth century, the expansion of industries resulted in management models based on standard operations and the analysis of time and methods (Cheng et al., 2011). In the post-World War II period, the growth of consumer demand resulted in the improvement of quality and best practices in operation management (Voss et al., 2002). At the end of the twentieth century, the growth of competition and diversity of consumer demand due to globalization resulted in manufacturing processes managed according to quality, cost, delivery, flexibility, speed and reliability indicators (Chowdary and George, 2012; Kim et al., 2015). According to Moyano-Fuentes and Sacristan-Díaz (2012), Lean Manufacturing (LM) has been widely applied in the management of manufacturing processes. To Ohno (1988), LM aimed for the elimination of activities and procedures that do not add value to the final product. Therefore, Chowdary and George (2012) enhanced the operational improvement in a company due to the implementation of LM practices. Reductions of waiting time, cycle time and inventory were among the improvements to manufacturing processes. Chen et al. (2010) presented a case study of the LM implementation in a factory in the USA. The use of the VSM tool resulted in reduced inventory and rework levels. In addition to the benefits of the production flow, Dues et al. (2013) commented that the use of LM tools also maximizes the gains in environmental and social areas of the manufacturing process. Because of this, many authors seek the integration of sustainability indicators into VSM. Paju et al. (2010) integrated Life Cycle Assessment (LCA) and Discrete Event Simulation (DES) into VSM. Faulkner and Badurdeen (2014) utilized a group of sustainability indicators integrated into VSM to assess the sustainability level in companies with different characteristics in relation to the production volumes and product varieties. The model used consumption indicators (water, energy and raw materials), noise level and ergonomic analysis of the workplace as sustainability indicators. Kuhlang et al.

Lean thinking is a production strategy that aims to increase profit, with limited resources. Just-intime (JIT) practices, waste reduction, improvement strategies, defect-free production and work standardization are the principal characteristics of lean thinking. The primary goal of lean production is to reduce costs and increase productivity by eliminating waste. Anything other than the minimum amount of equipment, materials, parts, space and employee time necessary to produce the required products is waste (Suzaki, 1987). Seven types of waste negatively affect the productivity of manufacturing companies: correction, overproduction, motion, material movement, waiting, inventory and processing. The presence of all seven types of waste negatively impacts the product lead-time, cost and quality (Walder et al., 2007). Several industries and manufacturing processes, from the automotive industry to the service industry, integrate their production strategies with lean thinking principles, aiming to improve productivity and quality through cost reduction. Previous studies have widely investigated the impact of human factors and worker behaviours on company performance and expected outcomes (Wygant et al., 1993; Resnick and Zanotti, 1997; Shikdar and Sawaqed, 2004; Dul et al., 2004; Othman et al., 2012; Xu et al., 2012). Based on such principles, the applied science of ergonomics analyses the importance of workstation and work process design and the effects on worker safety and health. Past and recent studies have widely discussed how ergonomics can optimize human performance and overall work system performance (Dul and Neumann, 2009). The design of ergonomic workplaces and jobs reduces injury and absenteeism rates, while improving productivity, quality and reliability (Botti et al., 2014). Previous studies have shown that musculoskeletal disorders (MSDs) lead to significant loss of productivity due to higher absenteeism and injury rates (Cheshmehgaz et al., 2012). Work-related MSDs are common occupational diseases among assembly workers due to repetitive motions or heavy workloads (Xu et al., 2012). Botti et al. (2015) proposed a mathematical model to design ergonomic job rotation policies in assembly lines, that ensures optimal person-job fit.

Nowadays enterprises are driven by a market demand characterized by fierce competition, rapid pace of business and continually compressed time schedules. On the one hand, manufacturing is experiencing shortened production cycles and reduced batch sizes; on the other hand, the variety of product types and their customization are increasing, as well as customer demands rapidly change. Hence, to maintain and improve their competitive advantage, leading organizations in different industrial sectors need to improve process optimization and efficiency. One initiative that a company may undertake is the implementation of lean manufacturing practices: this term has been introduced by Womack et al. [1] to describe the working philosophy deployed in Japanese companies, with particular concern for Toyota. This methodology relies on the elimination of wastes and non-productive processes, in order to focus on value added operations and produce high-quality products, at the customers demand pace, with ideally no waste. Another approach is the deployment of automation and Information Technology (IT) tools, which allow to improve process planning and control, as well as to enhance the performance of each step of the manufacturing process. The landscape of software classes and their purposes has been changing over the years, and is still evolving at a high pace. Today, the focus is on the integration and the communication between different information tools and among systems deployed by different companies (for example, among firms belonging to the same supply chain).

Lean over the years has become a “buzz” word. Started with lean manufacturing in the late 80s (rebranding the Toyota Production System) [1], and nowadays the term “Lean” can be found almost everywhere, just to offer some examples: lean services, lean entrepreneurship, lean software development, lean product development, lean accounting, lean startups and the list goes on and on. The underlying concept though is the same; maximize the customer value with minimum waste, i.e. “manufacturing / delivering more with less”. Although, the term “lean” is widely understood nowadays, implementing lean still poses a number of challenges. The successful lean transformation, as described the process of a company moving from an old way of thinking to lean thinking by lean experts and practitioners, relies in a big number of factors. The identification and ranking of these critical success factors have been the focus of a big number of studies. Salonitis and Tsinopoulos [2] based on an extensive review of the available literature, identified several key success factors, including: “Organisational culture and ownership”, “Developing organisational readiness”, “Management commitment and capability”, “Providing adequate resources to support change”, “External support from consultants in the first instance”, “Effective communication and engagement”, “Strategic approach to improvements”, “Teamwork and joined-up whole systems thinking”, and “Timing to set realistic timescales for change and to make effective use of commitments and enthusiasm for change”. Zargun and AlAshhab [3], in a similar study, identified 27 critical success factors that they classified into four groups, namely “Strategy and Objectives”, “Leadership and Management”, “Human resources” and “External factors”. The commitment of senior management in the lean transformation is underlined in almost all studies. Dombrowski and Mielke [4] highlighted the leadership as a cornerstone for engaging employees in continuous improvement initiatives, something that they consider a critical factor for introducing a lean production system. In the present paper, the focus is on the role of high level management in the successful implementation of lean manufacturing. The work is based on a systematic literature review and a number of interviews conducted in various manufacturing companies in the UK.

مقاله سال 2016

 مجله تحقیقات بازاریابی – Journal of Business Research

With intense competition as the new norm, productivity improvement activities are extremely important. Lean production (LP) is an example of a business system innovation intended to increase productivity. This study examines specific management communication practices that are present in LP, and conversely, specific practices that are absent from LP, but that are present in traditional non-LP contexts.

LP consists largely of improvement work and is dependent on a set of collective activities (e.g., Quality Circles, and Just-In-Time) to benefit the organization. Transferring new knowledge, such as LP, is a challenging task, and increased competition makes mastering that challenge important (Lindlöf, Söderberg, and Persson, 2013). According to Daniel, Myers, and Dixon (2012), adoption of innovations involves making them part of everyday routines. Mol and Birkinshaw (2009) argue for further research on adopting management innovations; while Liukkonen (1992) shows that high work productivity requires high engagement from workers and managers alike.

In the LP context, Worley and Doolen (2006) argue that management communication and support play an important role in LP implementation. Even though management communication practices are part of the innovations, limited research focuses on the granular level of communication practices. To address this lack of research, this study develops an understanding of management communication practices employed in the LP context.